All files / src/domains/recruitment/schemas screening-ai.schema.ts

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import { Prop, Schema, SchemaFactory } from '@nestjs/mongoose';
import { Document, Schema as MongooseSchema } from 'mongoose';
 
@Schema({ timestamps: true, collection: 'recruitment_screening_rules' })
export class ScreeningRule extends Document {
  @Prop({ required: true, index: true })
  tenantId: string;
 
  @Prop({ required: true })
  ruleName: string;
 
  @Prop({ required: true })
  criteriaType: string; // 'Skills' | 'Experience' | 'Education' | 'NoticePeriod' | 'Compensation'
 
  @Prop({ default: true })
  mandatory: boolean; // Acts as knockout criteria if unsatisfied
 
  @Prop({ default: 10 })
  weight: number; // For score calculations
}
 
export const ScreeningRuleSchema = SchemaFactory.createForClass(ScreeningRule);
 
@Schema({ timestamps: true, collection: 'ai_resume_analysis' })
export class AiResumeAnalysis extends Document {
  @Prop({ required: true, index: true })
  tenantId: string;
 
  @Prop({ required: true, type: MongooseSchema.Types.ObjectId, ref: 'CandidateResume' })
  resumeId: string;
 
  @Prop({ required: true })
  summaryText: string;
 
  @Prop({ type: [String], default: [] })
  identifiedSkills: string[];
 
  @Prop({ type: [String], default: [] })
  skillGaps: string[];
 
  @Prop({ default: 100 })
  matchScore: number;
 
  @Prop({ required: true })
  modelUsed: string;
 
  @Prop({ required: true })
  promptVersion: string;
 
  @Prop({ default: 0 })
  costTokens: number;
}
 
export const AiResumeAnalysisSchema = SchemaFactory.createForClass(AiResumeAnalysis);
AiResumeAnalysisSchema.index({ tenantId: 1, resumeId: 1 }, { unique: true });