content: package com.akto.test_editor.filter.data_operands_impl;
  
  import com.akto.dto.test_editor.DataOperandFilterRequest;
  import java.util.List;
  import java.util.Map;
  
  public class NlpClassificationFilter extends DataOperandsImpl {
  
      @Override
      public ValidationResult isValid(DataOperandFilterRequest dataOperandFilterRequest) {
          // TODO: MCP - Implement actual NLP classification logic here
          // For now, this is a demo placeholder that accepts all but validates nothing
          // Expected format in queryset: [category, threshold] like ["hate_speech", "0.65"]
          // OR nested format: {category: "hate_speech", gt: 0.65}
          
          // Get the data (payload content) - similar to magic implementation
          Object data = dataOperandFilterRequest.getData();
          Object querySetObj = dataOperandFilterRequest.getQueryset();
          
          if (data == null) {
              return new ValidationResult(false, "No data provided for NLP classification");
          }
          
          String dataString = data.toString();
          
          // TODO: MCP - Call actual NLP classification service on the dataString
          // The dataString should be analyzed for hate speech, toxicity, etc.
          // For demo purposes, always return false to indicate feature not implemented
          
          if (querySetObj instanceof List) {
              List<?> queryList = (List<?>) querySetObj;
              if (queryList.size() >= 2) {
                  String category = String.valueOf(queryList.get(0));
                  try {
                      double threshold = Double.parseDouble(String.valueOf(queryList.get(1)));
                      return new ValidationResult(false, "NLP Classification not yet implemented - demo mode. " +
                          "Category: " + category + ", Threshold: " + threshold + 
                          ", Data length: " + dataString.length());
                  } catch (NumberFormatException e) {
                      return new ValidationResult(false, "Invalid threshold format in NLP classification");
                  }
              }
          } else if (querySetObj instanceof Map) {
              Map<?, ?> queryMap = (Map<?, ?>) querySetObj;
              String category = String.valueOf(queryMap.get("category"));
              Object gtValue = queryMap.get("gt");
              Object ltValue = queryMap.get("lt");
              Object gteValue = queryMap.get("gte");
              Object lteValue = queryMap.get("lte");
              
              String operator = "unknown";
              double threshold = 0.0;
              
              if (gtValue != null) {
                  operator = "gt";
                  threshold = Double.parseDouble(String.valueOf(gtValue));
              } else if (ltValue != null) {
                  operator = "lt";
                  threshold = Double.parseDouble(String.valueOf(ltValue));
              } else if (gteValue != null) {
                  operator = "gte";
                  threshold = Double.parseDouble(String.valueOf(gteValue));
              } else if (lteValue != null) {
                  operator = "lte";
                  threshold = Double.parseDouble(String.valueOf(lteValue));
              }
              
              return new ValidationResult(false, "NLP Classification not yet implemented - demo mode. " +
                  "Category: " + category + ", Operator: " + operator + ", Threshold: " + threshold + 
                  ", Data length: " + dataString.length());
          }
          
          return new ValidationResult(false, "Invalid NLP classification parameters format");
      }
  }
  