qwen开源模型API详情

Python

示例代码

from openai import OpenAI
import os

def get_response():
    client = OpenAI(
        api_key=os.getenv("DASHSCOPE_API_KEY"), # 如果您没有配置环境变量，请在此处用您的API Key进行替换
        base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填写DashScope服务的base_url
    )
    completion = client.chat.completions.create(
        model="qwen2-72b-instruct",
        messages=[
            {'role': 'system', 'content': 'You are a helpful assistant.'},
            {'role': 'user', 'content': '你是谁？'}]
        )
    print(completion.model_dump_json())

if __name__ == '__main__':
    get_response()

返回结果

{
  "id": "chatcmpl-2399bcfb-6f3d-9269-bab2-7d2f4a68b3e5",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null,
      "message": {
        "content": "我是阿里云开发的一款超大规模语言模型，我叫通义千问。",
        "role": "assistant",
        "function_call": null,
        "tool_calls": null
      }
    }
  ],
  "created": 1721643915,
  "model": "qwen2-72b-instruct",
  "object": "chat.completion",
  "service_tier": null,
  "system_fingerprint": null,
  "usage": {
    "completion_tokens": 17,
    "prompt_tokens": 22,
    "total_tokens": 39
  }
}

curl

示例代码

curl --location "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen2-72b-instruct",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user", 
            "content": "你是谁？"
        }
    ]
}'

返回结果

{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": "我是阿里云开发的一款超大规模语言模型，我叫通义千问。"
      },
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null
    }
  ],
  "object": "chat.completion",
  "usage": {
    "prompt_tokens": 22,
    "completion_tokens": 17,
    "total_tokens": 39
  },
  "created": 1721643950,
  "system_fingerprint": null,
  "model": "qwen2-72b-instruct",
  "id": "chatcmpl-2b14edf9-c4c2-9e2c-a4e9-35fa3b7d1268"
}

Python

示例代码

import random
from http import HTTPStatus
# 建议dashscope SDK 的版本 >= 1.14.0
from dashscope import Generation


def call_with_messages():
    messages = [{'role': 'system', 'content': 'You are a helpful assistant.'},
                {'role': 'user', 'content': '你是谁？'}]
    response = Generation.call(model="qwen2-72b-instruct",
                               messages=messages,
                               # 将输出设置为"message"格式
                               result_format='message')
    if response.status_code == HTTPStatus.OK:
        print(response)
    else:
        print('Request id: %s, Status code: %s, error code: %s, error message: %s' % (
            response.request_id, response.status_code,
            response.code, response.message
        ))


if __name__ == '__main__':
    call_with_messages()

返回结果

{
  "status_code": 200,
  "request_id": "ac0a0baa-1033-903c-bb4f-9b2c52a0532c",
  "code": "",
  "message": "",
  "output": {
    "text": null,
    "finish_reason": null,
    "choices": [
      {
        "finish_reason": "stop",
        "message": {
          "role": "assistant",
          "content": "我是通义千问，由阿里云开发的AI助手。我被设计用来回答各种问题、提供信息和与用户进行对话。有什么我可以帮助你的吗？"
        }
      }
    ]
  },
  "usage": {
    "input_tokens": 22,
    "output_tokens": 36,
    "total_tokens": 58
  }
}

Java

示例代码

// Copyright (c) Alibaba, Inc. and its affiliates.
// 建议dashscope SDK的版本 >= 2.12.0
import java.util.Arrays;
import com.alibaba.dashscope.aigc.generation.Generation;
import com.alibaba.dashscope.aigc.generation.GenerationParam;
import com.alibaba.dashscope.aigc.generation.GenerationResult;
import com.alibaba.dashscope.common.Message;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.utils.JsonUtils;

public class Main {

    public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException {
        Generation gen = new Generation();

        Message systemMsg = Message.builder()
                .role(Role.SYSTEM.getValue())
                .content("You are a helpful assistant.")
                .build();

        Message userMsg = Message.builder()
                .role(Role.USER.getValue())
                .content("你是谁？")
                .build();

        GenerationParam param = GenerationParam.builder()
                .model("qwen2-72b-instruct")
                .messages(Arrays.asList(systemMsg, userMsg))
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .build();

        return gen.call(param);
    }

    public static void main(String[] args) {
        try {
            GenerationResult result = callWithMessage();
            System.out.println(JsonUtils.toJson(result));
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            // 使用日志框架记录异常信息
            // Logger.error("An error occurred while calling the generation service", e);
            System.err.println("An error occurred while calling the generation service: " + e.getMessage());
        }
        System.exit(0);
    }
}

返回结果

{
  "requestId": "bfd9d25a-f355-974d-ab02-b6ca306ebcba",
  "usage": {
    "input_tokens": 22,
    "output_tokens": 17,
    "total_tokens": 39
  },
  "output": {
    "choices": [
      {
        "finish_reason": "stop",
        "message": {
          "role": "assistant",
          "content": "我是阿里云开发的一款超大规模语言模型，我叫通义千问。"
        }
      }
    ]
  }
}

curl

示例代码

curl --location "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen2-72b-instruct",
    "input":{
        "messages":[      
            {
                "role": "system",
                "content": "You are a helpful assistant."
            },
            {
                "role": "user",
                "content": "你是谁？"
            }
        ]
    },
    "parameters": {
        "result_format": "message"
    }
}'

返回结果

{
  "output": {
    "choices": [
      {
        "finish_reason": "stop",
        "message": {
          "role": "assistant",
          "content": "我是阿里云开发的一款超大规模语言模型，我叫通义千问。"
        }
      }
    ]
  },
  "usage": {
    "total_tokens": 39,
    "output_tokens": 17,
    "input_tokens": 22
  },
  "request_id": "ff885277-3344-9bc6-b042-bf76454044ee"
}

Python

示例代码

from openai import OpenAI
import os

def get_response(messages):
    client = OpenAI(
        # 如果您没有配置环境变量，请在此处用您的API Key进行替换
        api_key=os.getenv("DASHSCOPE_API_KEY"), 
        # 填写DashScope服务的base_url
        base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    )
    completion = client.chat.completions.create(
        model="qwen2-72b-instruct",
        messages=messages
        )
    return completion

messages = [{'role': 'system', 'content': 'You are a helpful assistant.'}]
# 您可以自定义设置对话轮数，当前为3
for i in range(3):
    user_input = input("请输入：")
    # 将用户问题信息添加到messages列表中
    messages.append({'role': 'user', 'content': user_input})
    assistant_output = get_response(messages).choices[0].message.content
    # 将大模型的回复信息添加到messages列表中
    messages.append({'role': 'assistant', 'content': assistant_output})
    print(f'用户输入：{user_input}')
    print(f'模型输出：{assistant_output}')
    print('\n')

返回结果

curl

示例代码

curl --location "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen2-72b-instruct",
    "messages":[      
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user",
            "content": "你好"
        },
        {
            "role": "assistant",
            "content": "你好啊，我是通义千问。"
        },
        {
            "role": "user",
            "content": "你有哪些技能？"
        }
    ]
}'

返回结果

{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": "我有以下技能：\n1. 回答问题：我可以回答各种领域的问题，包括但不限于科学、技术、文化、历史、地理等等。\n2. 生成文本：我可以根据给定的提示或主题生成文章、故事、诗歌等文本内容。\n3. 翻译语言：我可以将文本从一种语言翻译成另一种语言，支持多种语言之间的互译。\n4. 编写代码：我可以编写简单的代码片段，帮助用户解决编程方面的问题。\n5. 提供建议：我可以为用户提供各种建议，如生活、学习、工作等方面的建议。\n6. 聊天互动：我可以与用户进行自然语言的对话，提供陪伴和娱乐。\n\n这些只是我的一些基本技能，实际上我可以做更多的事情。如果你有任何问题或需要帮助，随时可以问我！"
      },
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null
    }
  ],
  "object": "chat.completion",
  "usage": {
    "prompt_tokens": 43,
    "completion_tokens": 169,
    "total_tokens": 212
  },
  "created": 1721644509,
  "system_fingerprint": null,
  "model": "qwen2-72b-instruct",
  "id": "chatcmpl-c5e9a3e5-f327-9454-80d7-1a156f6c42a1"
}

Python

示例代码

from dashscope import Generation

def get_response(messages):
    response = Generation.call(model="qwen2-72b-instruct",
                               messages=messages,
                               # 将输出设置为"message"格式
                               result_format='message')
    return response


messages = [{'role': 'system', 'content': 'You are a helpful assistant.'}]

# 您可以自定义设置对话轮数，当前为3
for i in range(3):
    user_input = input("请输入：")
    # 将用户问题信息添加到messages列表中
    messages.append({'role': 'user', 'content': user_input})
    assistant_output = get_response(messages).output.choices[0]['message']['content']
    # 将大模型的回复信息添加到messages列表中
    messages.append({'role': 'assistant', 'content': assistant_output})
    print(f'用户输入：{user_input}')
    print(f'模型输出：{assistant_output}')
    print('\n')

返回结果

Java

示例代码

import java.util.ArrayList;
import java.util.List;
import com.alibaba.dashscope.aigc.generation.Generation;
import com.alibaba.dashscope.aigc.generation.GenerationParam;
import com.alibaba.dashscope.aigc.generation.GenerationResult;
import com.alibaba.dashscope.common.Message;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import java.util.Scanner;

public class Main {

    public static GenerationParam createGenerationParam(List<Message> messages) {
        return GenerationParam.builder()
                .model("qwen2-72b-instruct")
                .messages(messages)
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .build();
    }

    public static GenerationResult callGenerationWithMessages(GenerationParam param) throws ApiException, NoApiKeyException, InputRequiredException {
        Generation gen = new Generation();
        return gen.call(param);
    }

    public static void main(String[] args) {
        try {
            List<Message> messages = new ArrayList<>();

            messages.add(createMessage(Role.SYSTEM, "You are a helpful assistant."));
            for (int i = 0; i < 3;i++) {
                Scanner scanner = new Scanner(System.in);
                System.out.print("请输入：");
                String userInput = scanner.nextLine();
                if ("exit".equalsIgnoreCase(userInput)) {
                    break;
                }
                messages.add(createMessage(Role.USER, userInput));
                GenerationParam param = createGenerationParam(messages);
                GenerationResult result = callGenerationWithMessages(param);
                System.out.println("模型输出："+result.getOutput().getChoices().get(0).getMessage().getContent());
                messages.add(result.getOutput().getChoices().get(0).getMessage());
            }
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            e.printStackTrace();
        }
        System.exit(0);
    }

    private static Message createMessage(Role role, String content) {
        return Message.builder().role(role.getValue()).content(content).build();
    }
}

返回结果

curl

示例代码

curl --location "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen2-72b-instruct",
    "input":{
        "messages":[      
            {
                "role": "system",
                "content": "You are a helpful assistant."
            },
            {
                "role": "user",
                "content": "你好"
            },
            {
                "role": "assistant",
                "content": "你好啊，我是通义千问。"
            },
            {
                "role": "user",
                "content": "你有哪些技能？"
            }
        ]
    },
    "parameters": {
        "result_format": "message"
    }
}'

返回结果

{
  "output": {
    "choices": [
      {
        "finish_reason": "stop",
        "message": {
          "role": "assistant",
          "content": "我有以下技能：\n1. 回答问题：我可以回答各种领域的问题，包括但不限于科学、技术、文化、历史、地理等等。\n2. 提供信息：我可以提供实时天气、新闻、股票等信息。\n3. 生成文本：我可以根据给定的提示或主题生成各种类型的文本，如故事、诗歌、文章等等。\n4. 翻译语言：我可以翻译多种语言，包括但不限于中文、英文、法文、西班牙文等等。\n5. 编写代码：我可以编写和解释各种编程语言的代码，如Python、Java、C++等等。\n6. 提供建议：我可以提供各种生活、工作、学习等方面的建议和指导。\n\n总之，我的技能非常广泛，只要你需要，我都可以尽力帮助你。"
        }
      }
    ]
  },
  "usage": {
    "total_tokens": 206,
    "output_tokens": 163,
    "input_tokens": 43
  },
  "request_id": "7c55191a-6047-96d7-b068-e83bb0bc73ca"
}

Python

示例代码

from openai import OpenAI
import os

def get_response():
    client = OpenAI(
        api_key=os.getenv("DASHSCOPE_API_KEY"),
        base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    )
    completion = client.chat.completions.create(
        model="qwen2-72b-instruct",
        messages=[{'role': 'system', 'content': 'You are a helpful assistant.'},
                  {'role': 'user', 'content': '你是谁？'}],
        stream=True,
        # 可选，配置以后会在流式输出的最后一行展示token使用信息
        stream_options={"include_usage": True}
        )
    for chunk in completion:
        print(chunk.model_dump_json())

if __name__ == '__main__':
    get_response()

返回结果

{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"","function_call":null,"role":"assistant","tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"我是","function_call":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"阿里","function_call":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"云","function_call":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"开发的一款超大规模语言","function_call":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"模型，我叫通义千问","function_call":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[{"delta":{"content":"。","function_call":null,"role":null,"tool_calls":null},"finish_reason":"stop","index":0,"logprobs":null}],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a53dd104-38fc-998b-8d27-cc79d3b13b62","choices":[],"created":1721644687,"model":"qwen2-72b-instruct","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":{"completion_tokens":17,"prompt_tokens":22,"total_tokens":39}}

curl

示例代码

curl --location "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
    "model": "qwen2-72b-instruct",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user", 
            "content": "你是谁？"
        }
    ],
    "stream":true
}'

返回结果

data: {"choices":[{"delta":{"content":"","role":"assistant"},"index":0,"logprobs":null,"finish_reason":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: {"choices":[{"finish_reason":null,"delta":{"content":"我是"},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: {"choices":[{"delta":{"content":"阿里"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: {"choices":[{"delta":{"content":"云"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: {"choices":[{"delta":{"content":"开发的一款超大规模语言"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: {"choices":[{"delta":{"content":"模型，我叫通义千问"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: {"choices":[{"delta":{"content":"。"},"finish_reason":"stop","index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721644713,"system_fingerprint":null,"model":"qwen2-72b-instruct","id":"chatcmpl-4d54b51f-6896-93b2-a81b-07b88304ffc4"}

data: [DONE]

Python

示例代码

from http import HTTPStatus
from dashscope import Generation


def call_with_stream():
    messages = [
        {'role':'system','content':'you are a helpful assistant'},
        {'role': 'user','content': '你是谁？'}
        ]
    responses = Generation.call(
        model="qwen2-72b-instruct",
        messages=messages,
        # 设置输出为'message'格式
        result_format='message',
        # 设置输出方式为流式输出
        stream=True,
        # 增量式流式输出
        incremental_output=True
        )
    full_content = ""
    for response in responses:
        if response.status_code == HTTPStatus.OK:
            print(response)
            full_content += response.output.choices[0].message.content
        else:
            print('Request id: %s, Status code: %s, error code: %s, error message: %s' % (
                response.request_id, response.status_code,
                response.code, response.message
            ))
    print(f"Full content:{full_content}")

if __name__ == '__main__':
    call_with_stream()

返回结果

{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "我是"}}]}, "usage": {"input_tokens": 21, "output_tokens": 1, "total_tokens": 22}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "通"}}]}, "usage": {"input_tokens": 21, "output_tokens": 2, "total_tokens": 23}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "义"}}]}, "usage": {"input_tokens": 21, "output_tokens": 3, "total_tokens": 24}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "千问，由阿里"}}]}, "usage": {"input_tokens": 21, "output_tokens": 8, "total_tokens": 29}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "云开发的AI助手。我被"}}]}, "usage": {"input_tokens": 21, "output_tokens": 16, "total_tokens": 37}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "设计用来回答各种问题、提供信息"}}]}, "usage": {"input_tokens": 21, "output_tokens": 24, "total_tokens": 45}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": "和与用户进行对话。有什么我可以"}}]}, "usage": {"input_tokens": 21, "output_tokens": 32, "total_tokens": 53}}
{"status_code": 200, "request_id": "xxx", "code": "", "message": "", "output": {"text": null, "finish_reason": null, "choices": [{"finish_reason": "stop", "message": {"role": "assistant", "content": "帮助你的吗？"}}]}, "usage": {"input_tokens": 21, "output_tokens": 36, "total_tokens": 57}}

Java

示例代码

// Copyright (c) Alibaba, Inc. and its affiliates.

import java.util.Arrays;
import java.util.concurrent.Semaphore;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.concurrent.Semaphore;
import com.alibaba.dashscope.aigc.generation.Generation;
import com.alibaba.dashscope.aigc.generation.GenerationParam;
import com.alibaba.dashscope.aigc.generation.GenerationResult;
import com.alibaba.dashscope.common.Message;
import com.alibaba.dashscope.common.ResultCallback;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.InputRequiredException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.utils.JsonUtils;
import io.reactivex.Flowable;

public class Main {

    private static final Logger logger = LoggerFactory.getLogger(Main.class);

    private static void handleGenerationResult(GenerationResult message, StringBuilder fullContent) {
        fullContent.append(message.getOutput().getChoices().get(0).getMessage().getContent());
        logger.info("Received message: {}", JsonUtils.toJson(message));
    }

    public static void streamCallWithMessage(Generation gen, Message userMsg)
            throws NoApiKeyException, ApiException, InputRequiredException {
        GenerationParam param = buildGenerationParam(userMsg);
        Flowable<GenerationResult> result = gen.streamCall(param);
        StringBuilder fullContent = new StringBuilder();

        result.blockingForEach(message -> handleGenerationResult(message, fullContent));

        logger.info("Full content: \n{}", fullContent.toString());
    }

    public static void streamCallWithCallback(Generation gen, Message userMsg)
            throws NoApiKeyException, ApiException, InputRequiredException, InterruptedException {
        GenerationParam param = buildGenerationParam(userMsg);
        Semaphore semaphore = new Semaphore(0);
        StringBuilder fullContent = new StringBuilder();

        gen.streamCall(param, new ResultCallback<GenerationResult>() {
            @Override
            public void onEvent(GenerationResult message) {
                handleGenerationResult(message, fullContent);
            }

            @Override
            public void onError(Exception err) {
                logger.error("Exception occurred: {}", err.getMessage());
                semaphore.release();
            }

            @Override
            public void onComplete() {
                logger.info("Completed");
                semaphore.release();
            }
        });

        semaphore.acquire();
        logger.info("Full content: \n{}", fullContent.toString());
    }

    private static GenerationParam buildGenerationParam(Message userMsg) {
        return GenerationParam.builder()
                .model("qwen2-72b-instruct")
                .messages(Arrays.asList(userMsg))
                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
                .incrementalOutput(true)
                .build();
    }

    public static void main(String[] args) {
        try {
            Generation gen = new Generation();
            Message userMsg = Message.builder().role(Role.USER.getValue()).content("如何做西红柿炖牛腩？").build();

            streamCallWithMessage(gen, userMsg);
            streamCallWithCallback(gen, userMsg);
        } catch (ApiException | NoApiKeyException | InputRequiredException | InterruptedException e) {
            logger.error("An exception occurred: {}", e.getMessage());
        }
    }
}

返回结果

{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":1,"total_tokens":12},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"我是"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":2,"total_tokens":13},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"通"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":3,"total_tokens":14},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"义"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":8,"total_tokens":19},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"千问，由阿里"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":16,"total_tokens":27},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"云开发的AI助手。我被"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":24,"total_tokens":35},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"设计用来回答各种问题、提供信息"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":32,"total_tokens":43},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":"和与用户进行对话。有什么我可以"}}]}}
{"requestId":"xxx","usage":{"input_tokens":11,"output_tokens":36,"total_tokens":47},"output":{"choices":[{"finish_reason":"stop","message":{"role":"assistant","content":"帮助你的吗？"}}]}}

curl

示例代码

curl --location "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--header "X-DashScope-SSE: enable" \
--data '{
    "model": "qwen2-72b-instruct",
    "input":{
        "messages":[      
            {
                "role": "system",
                "content": "You are a helpful assistant."
            },
            {
                "role": "user",
                "content": "你是谁？"
            }
        ]
    },
    "parameters": {
        "result_format": "message",
        "incremental_output":true
    }
}'

返回结果

id:1
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"我是","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":23,"input_tokens":22,"output_tokens":1},"request_id":"xxx"}

id:2
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"通","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":24,"input_tokens":22,"output_tokens":2},"request_id":"xxx"}

id:3
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"义","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":25,"input_tokens":22,"output_tokens":3},"request_id":"xxx"}

id:4
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"千问，由阿里","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":30,"input_tokens":22,"output_tokens":8},"request_id":"xxx"}

id:5
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"云开发的AI助手。我被","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":38,"input_tokens":22,"output_tokens":16},"request_id":"xxx"}

id:6
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"设计用来回答各种问题、提供信息","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":46,"input_tokens":22,"output_tokens":24},"request_id":"xxx"}

id:7
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"和与用户进行对话。有什么我可以","role":"assistant"},"finish_reason":"null"}]},"usage":{"total_tokens":54,"input_tokens":22,"output_tokens":32},"request_id":"xxx"}

id:8
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":"帮助你的吗？","role":"assistant"},"finish_reason":"stop"}]},"usage":{"total_tokens":58,"input_tokens":22,"output_tokens":36},"request_id":"xxx"}