大模型调用

智谱AI

智普AI 我们这边可以使用GLM-4-Flash,免费的但是会限制速率

需要先申请Key，https://www.bigmodel.cn/usercenter/proj-mgmt/apikeys

初次注册会送免费的token

1. Token Utils

package icu.flycode.sdk.utils;

import com.auth0.jwt.JWT;
import com.auth0.jwt.algorithms.Algorithm;
import com.google.common.cache.Cache;
import com.google.common.cache.CacheBuilder;

import java.nio.charset.StandardCharsets;
import java.util.Calendar;
import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.TimeUnit;

public class BearerTokenUtils {

    // 过期时间；默认30分钟
    private static final long EXPIRE_MILLIS = 30 * 60 * 1000L;

    // 缓存服务
    public static Cache<String, String> cache = CacheBuilder.newBuilder()
            .expireAfterWrite(EXPIRE_MILLIS - (60 * 1000L), TimeUnit.MILLISECONDS)
            .build();

    public static String getToken(String apiKeySecret) {
        String[] split = apiKeySecret.split("\\.");
        return getToken(split[0], split[1]);
    }

    /**
     * 对 ApiKey 进行签名
     *
     * @param apiKey    登录创建 ApiKey <a href="https://open.bigmodel.cn/usercenter/apikeys">apikeys</a>
     * @param apiSecret apiKey的后半部分 828902ec516c45307619708d3e780ae1.w5eKiLvhnLP8MtIf 取 w5eKiLvhnLP8MtIf 使用
     * @return Token
     */
    public static String getToken(String apiKey, String apiSecret) {
        // 缓存Token
        String token = cache.getIfPresent(apiKey);
        if (null != token) {
            return token;
        }
        // 创建Token
        Algorithm algorithm = Algorithm.HMAC256(apiSecret.getBytes(StandardCharsets.UTF_8));
        Map<String, Object> payload = new HashMap<>();
        payload.put("api_key", apiKey);
        payload.put("exp", System.currentTimeMillis() + EXPIRE_MILLIS);
        payload.put("timestamp", Calendar.getInstance().getTimeInMillis());
        Map<String, Object> headerClaims = new HashMap<>();
        headerClaims.put("alg", "HS256");
        headerClaims.put("sign_type", "SIGN");
        token = JWT.create().withPayload(payload).withHeader(headerClaims).sign(algorithm);
        cache.put(apiKey, token);
        return token;
    }
}

2. 生成Token

public class ApiTest {
    public static void main(String[] args) {
        String apiKey = "xxxx";
        String token = BearerTokenUtils.getToken(apiKey);
        System.out.println(token);
    }
}

这个生成的token会在调用的时候需要

3. 编写curl脚本

curl -X POST \
        -H "Authorization: Bearer token" \
        -H "Content-Type: application/json" \
        -H "User-Agent: Mozilla/4.0 (compatible; MSIE 5.0; Windows NT; DigExt)" \
        -d '{
          "model":"glm-4",
          "stream": "true",
          "messages": [
              {
                  "role": "user",
                  "content": "1+1"
              }
          ]
        }' \
  https://open.bigmodel.cn/api/paas/v4/chat/completions

将上面的curl脚本使用ApiFox或者其他方式请求数据

4. Java测试代码

主要步骤如下：

构造http发送请求，格式如上面的curl
解析返回的数据

    @Test
    public void test_http() throws IOException {
        String apiKey = "xxxxxx";
        String token = BearerTokenUtils.getToken(apiKey);

        URL url = new URL("  https://open.bigmodel.cn/api/paas/v4/chat/completions");
        HttpsURLConnection httpsURLConnection = (HttpsURLConnection) url.openConnection();
        httpsURLConnection.setRequestMethod("POST");
        httpsURLConnection.setRequestProperty("Authorization", "Bearer " + token);
        httpsURLConnection.setRequestProperty("Content-Type", "application/json");
        httpsURLConnection.setRequestProperty("User-Agent", "Mozilla/4.0 (compatible; MSIE 5.0; Windows NT; DigExt)");
        httpsURLConnection.setDoOutput(true);

        String code = "print('Hello, World!')";
        String jsonInputString = "{"
                + "\"model\":\"glm-4-flash\","
                + "\"messages\": ["
                + "    {"
                + "        \"role\": \"user\","
                + "        \"content\": \"你是一个高级编程架构师，精通各类场景方案、架构设计和编程语言，根据用户提交的代码分析给出解决方案。代码为: " + code + "\""
                + "    }"
                + "]"
                + "}";


        try (OutputStream os = httpsURLConnection.getOutputStream()) {
            byte[] input = jsonInputString.getBytes("utf-8");
            os.write(input, 0, input.length);
        }

        int responseCode = httpsURLConnection.getResponseCode();
        System.out.println(responseCode);

        BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(httpsURLConnection.getInputStream()));
        String line;
        StringBuilder content = new StringBuilder();
        while ((line = bufferedReader.readLine()) != null) {
            content.append(line);
        }

        bufferedReader.close();
        httpsURLConnection.disconnect();
        System.out.println(content);
    }

我们只需要将里面的内容转换为实体对象，即可获取content内容。

5. 编写模型发送响应实体类

package icu.flycode.sdk.domain.models;

public enum Model {

    @Deprecated
    CHATGLM_6B_SSE("chatGLM_6b_SSE", "ChatGLM-6B 测试模型"),
    @Deprecated
    CHATGLM_LITE("chatglm_lite", "轻量版模型，适用对推理速度和成本敏感的场景"),
    @Deprecated
    CHATGLM_LITE_32K("chatglm_lite_32k", "标准版模型，适用兼顾效果和成本的场景"),
    @Deprecated
    CHATGLM_STD("chatglm_std", "适用于对知识量、推理能力、创造力要求较高的场景"),
    @Deprecated
    CHATGLM_PRO("chatglm_pro", "适用于对知识量、推理能力、创造力要求较高的场景"),
    /** 智谱AI 23年06月发布 */
    CHATGLM_TURBO("chatglm_turbo", "适用于对知识量、推理能力、创造力要求较高的场景"),
    /** 智谱AI 24年01月发布 */
    GLM_3_5_TURBO("glm-3-turbo","适用于对知识量、推理能力、创造力要求较高的场景"),
    GLM_4("glm-4","适用于复杂的对话交互和深度内容创作设计的场景"),
    GLM_4V("glm-4v","根据输入的自然语言指令和图像信息完成任务，推荐使用 SSE 或同步调用方式请求接口"),
    GLM_4_FLASH("glm-4-flash","适用简单任务，速度最快，价格最实惠的版本，具有128k上下文"),
    COGVIEW_3("cogview-3","根据用户的文字描述生成图像,使用同步调用方式请求接口"),
    ;
    private final String code;
    private final String info;

    Model(String code, String info) {
        this.code = code;
        this.info = info;
    }

    public String getCode() {
        return code;
    }

    public String getInfo() {
        return info;
    }
}

发送请求设置角色

import java.util.List;

public class ChatCompletionRequest {

    private String model = Model.GLM_4_FLASH.getCode();
    private List<Prompt> messages;

    public static class Prompt {
        private String role;
        private String content;

        public Prompt() {
        }

        public Prompt(String role, String content) {
            this.role = role;
            this.content = content;
        }

        public String getRole() {
            return role;
        }

        public void setRole(String role) {
            this.role = role;
        }

        public String getContent() {
            return content;
        }

        public void setContent(String content) {
            this.content = content;
        }

    }

    public String getModel() {
        return model;
    }

    public void setModel(String model) {
        this.model = model;
    }

    public List<Prompt> getMessages() {
        return messages;
    }

    public void setMessages(List<Prompt> messages) {
        this.messages = messages;
    }
}

获取响应

package icu.flycode.sdk.domain.models;

import java.util.List;

public class ChatCompletionSyncResponse {

    private List<Choice> choices;

    public static class Choice {
        private Message message;

        public Message getMessage() {
            return message;
        }

        public void setMessage(Message message) {
            this.message = message;
        }
    }

    public static class Message {
        private String role;
        private String content;

        public String getRole() {
            return role;
        }

        public void setRole(String role) {
            this.role = role;
        }

        public String getContent() {
            return content;
        }

        public void setContent(String content) {
            this.content = content;
        }
    }

    public List<Choice> getChoices() {
        return choices;
    }

    public void setChoices(List<Choice> choices) {
        this.choices = choices;
    }
}

6. 修改测试代码

    public static void main(String[] args) throws Exception {
        System.out.println("测试执行");
        // 代码评审
        // 1. 读取Git Diff更改记录
        ProcessBuilder processBuilder = new ProcessBuilder("git", "diff", "HEAD~1", "HEAD");
        processBuilder.directory(new File("."));
        Process process = processBuilder.start();

        // 读取输出流
        BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(process.getInputStream()));
        String line;
        StringBuilder diffStr = new StringBuilder();
        while ((line = bufferedReader.readLine()) != null) {
            diffStr.append(line);
        }

        // 2. 获取退出码
        int exitCode = process.waitFor();
        System.out.println("Exited with code: " + exitCode);
        // 3. 返回读取数据
        System.out.println("diff code: " + diffStr.toString());


        // 4. 调用OpenAI API进行代码评审
        String codedReview = codeReview(diffStr.toString());
        System.out.println("Code review: " + codedReview);
    }


    private static String codeReview(String diffCode) throws Exception {
        String apiKey = "046183b32b904844949bd062b1ab223c.MEgwXNBvYeLMvd51";
        String token = BearerTokenUtils.getToken(apiKey);

        HttpsURLConnection httpsURLConnection = getHttpsURLConnection(token);


        ChatCompletionRequest chatCompletionRequest = new ChatCompletionRequest();
        chatCompletionRequest.setModel(Model.GLM_4_FLASH.getCode());
        chatCompletionRequest.setMessages(new ArrayList<ChatCompletionRequest.Prompt>(){
            {
                add(new ChatCompletionRequest.Prompt("user","你是一个高级编程架构师，精通各类场景方案、架构设计和编程语言请，请您根据git diff记录，对代码做出评审。代码为: "));
                add(new ChatCompletionRequest.Prompt("user",diffCode));
            }
        });

        try (OutputStream os = httpsURLConnection.getOutputStream()) {
            byte[] input = JSON.toJSONString(chatCompletionRequest).getBytes(StandardCharsets.UTF_8);
            os.write(input, 0, input.length);
        }

        int responseCode = httpsURLConnection.getResponseCode();
        System.out.println(responseCode);

        BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(httpsURLConnection.getInputStream()));
        String line;
        StringBuilder content = new StringBuilder();
        while ((line = bufferedReader.readLine()) != null) {
            content.append(line);
        }

        bufferedReader.close();
        httpsURLConnection.disconnect();

        System.out.println(content);
        ChatCompletionSyncResponse chatCompletionSyncResponse = JSON.parseObject(content.toString(), ChatCompletionSyncResponse.class);
        String returnContent = chatCompletionSyncResponse.getChoices().get(0).getMessage().getContent();

        return returnContent;
    }

    private static HttpsURLConnection getHttpsURLConnection(String token) throws IOException {
        URL url = new URL("https://open.bigmodel.cn/api/paas/v4/chat/completions");
        HttpsURLConnection httpsURLConnection = (HttpsURLConnection) url.openConnection();
        httpsURLConnection.setRequestMethod("POST");
        httpsURLConnection.setRequestProperty("Authorization", "Bearer " + token);
        httpsURLConnection.setRequestProperty("Content-Type", "application/json");
        httpsURLConnection.setRequestProperty("User-Agent", "Mozilla/4.0 (compatible; MSIE 5.0; Windows NT; DigExt)");
        httpsURLConnection.setDoOutput(true);
        return httpsURLConnection;
    }

智谱AI

1. Token Utils

2. 生成Token

3. 编写curl脚本

4. Java测试代码

5. 编写模型发送响应实体类

6. 修改测试代码

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