package com.njuzr.eaibackend.service;

import com.fasterxml.jackson.annotation.JsonProperty;
import com.njuzr.eaibackend.exception.MyException;
import com.njuzr.eaibackend.po.AIEntry;
import com.njuzr.eaibackend.utils.WebClientUtil;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.http.HttpStatus;
import org.springframework.stereotype.Service;

import java.util.List;

/**
 * @author: Leonezhurui
 * @Date: 2024/3/2 - 00:00
 * @Package: EAI-Backend
 */

@Slf4j
@Service
public class AIRequestService {

    @Value("${openai.chatgpt.model}")
    private String model;

    @Value("${openai.chatgpt.api.key}")
    private String key;

    private final WebClientUtil chatgptClient;
    private final WebClientUtil chatglmClient;
    private final WebClientUtil qwenClient;

    private final String prefix = "/v1/chat/completions";


    @Value("${config.llm.ChatGLM3.url}")
    private String glm3Url;

    @Value("${config.llm.ChatGLM4.url}")
    private String glm4Url;

    @Value("${config.llm.ChatGLM4.token}")
    private String glm4Token;

    @Value("${config.llm.ChatGLM4.modelName}")
    private String glm4ModelName;

    @Value("${config.llm.QWen14B.url}")
    private String qWen14BUrl;

    @Value("${config.llm.PreSentenceWorkflowChatGLM4.url}")
    private String preSentenceWorkflowglm4Url;

    @Value("${config.llm.PreSentenceWorkflowChatGLM4.token}")
    private String preSentenceWorkflowglm4Token;

    public AIRequestService(WebClientUtil chatgptClient, WebClientUtil chatglmClient, WebClientUtil qwenClient) {
        this.chatgptClient = chatgptClient;
        this.chatglmClient = chatglmClient;
        this.qwenClient = qwenClient;
    }

    public AIResponse requestChatGPT(List<AIEntry> messages) {
        MyRequestObject requestObject = new MyRequestObject(model, messages,0.7);
        String chatgptUrl = "https://api.openai.com";
        try {
            return chatgptClient.postWithToken(chatgptUrl+prefix, requestObject, AIResponse.class, key);
        } catch (Exception e) {
            log.error("WebClient请求失败，AI请求失败~");
            throw new MyException(HttpStatus.INTERNAL_SERVER_ERROR.value(), HttpStatus.INTERNAL_SERVER_ERROR.getReasonPhrase()+"："+"服务器请求AI出错");
        }
    }


    public AIResponse requestChatGLM(List<AIEntry> messages) {
        MyRequestObject requestObject = new MyRequestObject("ChatGLM3", messages,0.7);
        String url = glm3Url;

        try {
            return chatglmClient.post(url+prefix, requestObject, AIResponse.class);
        } catch (Exception e) {
            log.error("WebClient请求失败，AI请求失败~");
            throw new MyException(HttpStatus.INTERNAL_SERVER_ERROR.value(), HttpStatus.INTERNAL_SERVER_ERROR.getReasonPhrase()+"："+"服务器请求AI出错");
        }
    }


    public AIResponse requestChatGLM4(List<AIEntry> messages) {
        MyRequestObject requestObject = new MyRequestObject(glm4ModelName, messages,0.7);
        String url = glm4Url;

        try {
            return chatglmClient.postWithToken(url+prefix, requestObject, AIResponse.class, glm4Token);
        } catch (Exception e) {
            e.printStackTrace();
            log.error("WebClient请求失败，AI请求失败~"+e.getMessage());
            throw new MyException(HttpStatus.INTERNAL_SERVER_ERROR.value(), HttpStatus.INTERNAL_SERVER_ERROR.getReasonPhrase()+"："+"服务器请求AI出错");
        }
    }


    public AIResponse requestQWen(List<AIEntry> messages) {
        MyRequestObject requestObject = new MyRequestObject("QWen14B", messages,0.7);
        String url = qWen14BUrl;

        try {
            return qwenClient.post(url+prefix, requestObject, AIResponse.class);
        } catch (Exception e) {
            log.error("WebClient请求失败，AI请求失败~");
            throw new MyException(HttpStatus.INTERNAL_SERVER_ERROR.value(), HttpStatus.INTERNAL_SERVER_ERROR.getReasonPhrase()+"："+"服务器请求AI出错");
        }
    }

    public WorkflowRunResponse requestPreSentenceWorkflowWithRetry(String content, String assignmentDescription, String sentence) {
        int retry = 0;
        while (retry < 3) {
                WorkflowRunResponse response = requestPreSentenceWorkflow(content, assignmentDescription, sentence);
                if (response == null) {
                    log.error("requestPreSentenceWorkflowWithRetry failed, retry: {}/{}", retry+1, 3);
                    retry++;
                    continue;
                }
                return response;
        }
        throw new MyException(HttpStatus.INTERNAL_SERVER_ERROR.value(), HttpStatus.INTERNAL_SERVER_ERROR.getReasonPhrase()+"AI请求失败");
    }

    public WorkflowRunResponse requestPreSentenceWorkflow(String content, String assignmentDescription, String sentence) {
        MyWorkflowRequestInput input = new MyWorkflowRequestInput(content, assignmentDescription,sentence);
        MyWorkflowRequestObject requestObject = new MyWorkflowRequestObject("abc-1234", "blocking", input);
        String url = preSentenceWorkflowglm4Url;

        try {
            return chatglmClient.postWithToken(url, requestObject, WorkflowRunResponse.class, preSentenceWorkflowglm4Token);
        } catch (Exception e) {
            log.error("requestPreSentenceWorkflow failed, reason: {}", e.getMessage());
            return null;
        }
    }

    @Data
    @AllArgsConstructor
    static class MyWorkflowRequestObject {
        private String user;
        private String response_mode;
        private MyWorkflowRequestInput inputs;

    }

    @Data
    @AllArgsConstructor
    static class MyWorkflowRequestInput {
        private String content;
        private String assignment_description;
        private String sentence;
    }

    @Data
    static class WorkflowRunResponse {
        private String task_id;
        private String workflow_run_id;
        private WorkflowRunData data;
    }

    @Data
    static
    class WorkflowRunData {
        private String id;
        private String workflow_id;
        private String status;
        private Outputs outputs;
        private Object error;
        private double elapsed_time;
        private int total_tokens;
        private int total_steps;
        private long created_at;
        private long finished_at;
    }

    @Data
    static
    class Outputs {
        private String result_type;
        private String result_category;
        private String result_content;
    }

    @Data
    @AllArgsConstructor
    static class MyRequestObject {
        private String model;
        private List<AIEntry> messages;
        private Double temperature;
    }

    @Data
    public static class AIResponse {
        private String id;
        private List<Choice> choices;
        private Long created;
        private String model;
        private String object;
        private String system_fingerprint;
        private Usage usage;
    }

    @Data
    public static class Choice {
        private String finish_reason;
        private int index;
        private String logprobs;
        private ResponseMessage message;
    }

    @Data
    public static class ResponseMessage {
        private String content; // AI生成的回复
        private String role;
        private String function_call;
        private List<String> tool_calls;
    }

    @Data
    public static class Usage {
        private int completion_tokens;
        private int prompt_tokens;
        private int total_tokens;
    }
}