188 lines
7.5 KiB
Java
188 lines
7.5 KiB
Java
package com.rj.controller;
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import com.rj.dto.CommunityFeedDTO;
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import com.rj.dto.DifyWorkflowRequestDto;
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import com.rj.dto.DifyWorkflowResponseDto;
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import com.rj.dto.CustomerProfileAnalysisRequestDto;
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import com.rj.service.DifyWorkflowService;
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import io.swagger.v3.oas.annotations.Operation;
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import io.swagger.v3.oas.annotations.tags.Tag;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.http.ResponseEntity;
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import org.springframework.web.bind.annotation.*;
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import jakarta.validation.Valid;
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import java.util.HashMap;
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import java.util.Map;
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/**
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* Dify工作流控制器
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*
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* @author 李中华
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* @date 2025/1/3
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*/
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@Slf4j
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@RestController
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@RequestMapping("/api/aicommunity")
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@Tag(name = "Dify工作流", description = "Dify工作流API接口")
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public class DifyWorkflowController {
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@Autowired
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private DifyWorkflowService difyWorkflowService;
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/**
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* 企微对话分析工作流
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*/
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@PostMapping("/workflow/consulting-scenario")
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@Operation(summary = "企微对话分析工作流", description = "调用Dify企微对话分析工作流")
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public ResponseEntity<DifyWorkflowResponseDto> consultingScenarioWorkflow(
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@Valid @RequestBody DifyWorkflowRequestDto requestDto) {
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try {
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log.info("开始调用企微对话分析工作流， 参数： "+requestDto.toString());
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// 构建工作流输入参数
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Map<String, Object> inputs = new HashMap<>();
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inputs.put("unionId", requestDto.getUnionId());
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inputs.put("consultantId", requestDto.getConsultantId());
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inputs.put("communicateDate", requestDto.getCommunicateDate());
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inputs.put("analysisScene", requestDto.getAnalysisScene());
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inputs.put("aiAnalysisRequestId", requestDto.getAiAnalysisRequestId());
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inputs.put("version", requestDto.getVersion());
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inputs.put("chat", requestDto.getChat());
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// 创建请求对象
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DifyWorkflowService.DifyWorkflowRequest request =
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new DifyWorkflowService.DifyWorkflowRequest(inputs, requestDto.getConsultantId());
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// 调用工作流（Service层会自动保存数据到数据库）
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DifyWorkflowService.DifyWorkflowResponse response =
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difyWorkflowService.callConsultingScenarioWorkflow(request);
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// 构建返回结果
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DifyWorkflowResponseDto result = DifyWorkflowResponseDto.success(
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response.getWorkflowRunId(),
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response.getTaskId(),
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response.getData(),
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response.getMetadata()
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);
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return ResponseEntity.ok(result);
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} catch (Exception e) {
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log.error("调用企微对话分析工作流失败", e);
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DifyWorkflowResponseDto errorResult = DifyWorkflowResponseDto.failure(
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"工作流调用失败: " + e.getMessage(),
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e.getClass().getSimpleName()
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);
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return ResponseEntity.status(500).body(errorResult);
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}
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}
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/**
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* DCC对话分析工作流
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*/
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@PostMapping("/workflow/dcc-scenario")
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@Operation(summary = "DCC对话分析工作流", description = "调用Dify DCC对话分析工作流")
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public ResponseEntity<DifyWorkflowResponseDto> dccScenarioWorkflow(
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@Valid @RequestBody DifyWorkflowRequestDto requestDto) {
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try {
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log.info("开始调用DCC对话分析工作流，参数： " + requestDto.toString());
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// 构建工作流输入参数
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Map<String, Object> inputs = new HashMap<>();
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inputs.put("unionId", requestDto.getUnionId());
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inputs.put("consultantId", requestDto.getConsultantId());
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inputs.put("communicateDate", requestDto.getCommunicateDate());
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inputs.put("analysisScene", requestDto.getAnalysisScene());
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inputs.put("aiAnalysisRequestId", requestDto.getAiAnalysisRequestId());
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inputs.put("version", requestDto.getVersion());
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inputs.put("chat", requestDto.getChat());
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// 创建请求对象
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DifyWorkflowService.DifyWorkflowRequest request =
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new DifyWorkflowService.DifyWorkflowRequest(inputs, requestDto.getConsultantId());
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// 调用DCC工作流（Service层会自动保存数据到数据库）
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DifyWorkflowService.DifyWorkflowResponse response =
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difyWorkflowService.callDCCScenarioWorkflow(request);
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// 构建返回结果
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DifyWorkflowResponseDto result = DifyWorkflowResponseDto.success(
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response.getWorkflowRunId(),
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response.getTaskId(),
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response.getData(),
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response.getMetadata()
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);
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return ResponseEntity.ok(result);
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} catch (Exception e) {
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log.error("调用DCC对话分析工作流失败", e);
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DifyWorkflowResponseDto errorResult = DifyWorkflowResponseDto.failure(
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"DCC工作流调用失败: " + e.getMessage(),
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e.getClass().getSimpleName()
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);
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return ResponseEntity.status(500).body(errorResult);
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}
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}
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/**
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* 客户画像分析工作流
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*/
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@PostMapping("/workflow/customer-profile-analysis")
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@Operation(summary = "客户画像分析工作流", description = "调用Dify客户画像分析工作流")
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public ResponseEntity<DifyWorkflowResponseDto> customerProfileAnalysisWorkflow(
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@Valid @RequestBody CustomerProfileAnalysisRequestDto requestDto) {
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try {
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log.info("开始调用客户画像分析工作流，参数： " + requestDto.toString());
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// 构建工作流输入参数
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Map<String, Object> inputs = new HashMap<>();
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inputs.put("chat", requestDto.getChat());
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inputs.put("communicateDate", requestDto.getCommunicateDate());
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inputs.put("analysisScene", requestDto.getAnalysisScene());
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inputs.put("aiAnalysisRequestld", requestDto.getAiAnalysisRequestId()); // 注意：Dify工作流期望的参数名是aiAnalysisRequestld
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inputs.put("businessId", requestDto.getBusinessId());
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inputs.put("customerFlowId", requestDto.getCustomerFlowId());
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inputs.put("businessType", requestDto.getBusinessType());
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// 创建请求对象
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DifyWorkflowService.DifyWorkflowRequest request =
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new DifyWorkflowService.DifyWorkflowRequest(inputs, requestDto.getBusinessId());
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// 调用客户画像分析工作流（Service层会自动保存数据到数据库）
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DifyWorkflowService.DifyWorkflowResponse response =
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difyWorkflowService.callCustomerProfileAnalysisWorkflow(request);
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// 构建返回结果
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DifyWorkflowResponseDto result = DifyWorkflowResponseDto.success(
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response.getWorkflowRunId(),
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response.getTaskId(),
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response.getData(),
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response.getMetadata()
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);
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return ResponseEntity.ok(result);
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} catch (Exception e) {
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log.error("调用客户画像分析工作流失败", e);
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DifyWorkflowResponseDto errorResult = DifyWorkflowResponseDto.failure(
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"客户画像分析工作流调用失败: " + e.getMessage(),
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e.getClass().getSimpleName()
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);
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return ResponseEntity.status(500).body(errorResult);
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}
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}
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}
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