接下來我們要實作gpt的API Client及Service，並接到gpt返回的結果

我們可以先使用postman來測試API請求是否成功，成功後就可以在專案中實作各種方法

GPTApiClient

這裡我們存放所需的base_url、key，以及其他啟動服務所需的方法

public class GPTApiClient {
    private static final String API_TOKEN = "sk-proj-2kKxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx";
    private static final GPTApiClient GPTApiInstance = new GPTApiClient();
    private final GPTApiService gptApiService;
    public GPTApiClient(){
        // 創建一個OkHttpClient實例，並設置一個Interceptor，用於在每個請求中添加Authorization header
        OkHttpClient okHttpClient = new OkHttpClient.Builder()
                .connectTimeout(10, TimeUnit.SECONDS)
                .readTimeout(20, TimeUnit.SECONDS)
                .addInterceptor(new HttpLoggingInterceptor().setLevel(HttpLoggingInterceptor.Level.BODY))
                .addInterceptor(new Interceptor() {
                    @NotNull
                    @Override
                    public Response intercept(@NotNull Chain chain) throws IOException {
                        Request originalRequest = chain.request();
                        // 使用新的Request.Builder創建一個請求，將token添加到header中
                        Request newRequest = originalRequest.newBuilder()
                                .header("Authorization", "Bearer " + API_TOKEN)
                                .build();
                        return chain.proceed(newRequest);
                    }
                })
                .build();

        Retrofit retrofit = new Retrofit.Builder()
                .baseUrl("https://api.openai.com/")
                .addConverterFactory(GsonConverterFactory.create())
                .addCallAdapterFactory(RxJava3CallAdapterFactory.create())
                .client(okHttpClient)
                .build();
        gptApiService = retrofit.create(GPTApiService.class);

    }
    public static GPTApiClient getGPTApiInstance() {
        return GPTApiInstance;
    }

    public GPTApiService getGPTApiService(){
        return gptApiService;
    }
}

GPTApiService

這邊可以透過request及路徑來請求

public interface GPTApiService {
    @POST("v1/chat/completions")
    Observable<Response<GPTApiRespond>> getChatGPTRespond(@Body GPTApiRequest gptRequest);
}

GPTApiRequest

這裡存放請求的資料，包括一些gpt常用的參數，可以至官方的說明文件查看

public class GPTApiRequest {
    private final String model = "gpt-4o-mini";
    private List<ChatMessage> messages;
    private final Double temperature = 0.1;
    private final Integer max_tokens = 1000;
    private final Integer top_p = 1;
    private final Integer frequency_penalty = 0;
    private final Integer presence_penalty = 0;
    public void setMessages(List<ChatMessage> messages) {
        this.messages = messages;
    }

    public List<ChatMessage> getMessages() {
        return messages;
    }
    public static class ChatMessage {
        private String role;
        private String content;

        public ChatMessage(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;
        }
    }
}

GPTApiRespond

這裡處理請求成功後回傳的資料，主要使用到getContent()部分取得內容

public class GPTApiRespond {
    public Error error;
    public String id;
    public String object;
    public int created;
    public String model;
    public ArrayList<Choice> choices;
    public Usage usage;
    public String getId() {
        return id;
    }

    public void setId(String id) {
        this.id = id;
    }

    public String getObject() {
        return object;
    }

    public void setObject(String object) {
        this.object = object;
    }

    public int getCreated() {
        return created;
    }

    public void setCreated(int created) {
        this.created = created;
    }

    public String getModel() {
        return model;
    }

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

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

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

    public Usage getUsage() {
        return usage;
    }

    public void setUsage(Usage usage) {
        this.usage = usage;
    }
    public static class Error{
        public String message;

        public String getMessage() {
            return message;
        }

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

    public static class Choice{
        public int index;
        public String text;
        public Message message;
        public Object logprobs;
        public String finish_reason;

        public int getIndex() {
            return index;
        }

        public void setIndex(int index) {
            this.index = index;
        }

        public Object getLogprobs() {
            return logprobs;
        }

        public void setLogprobs(Object logprobs) {
            this.logprobs = logprobs;
        }

        public String getFinish_reason() {
            return finish_reason;
        }

        public void setFinish_reason(String finish_reason) {
            this.finish_reason = finish_reason;
        }

        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 static class Usage{
        public int prompt_tokens;
        public int completion_tokens;
        public int total_tokens;
    }
}

這樣在專案中onNext()方法就會收到資料了，下篇我們再來介紹提示詞的寫法，以及測試的成果