AI Job Matching

type MatchResult struct {
    MatchScore int      `json:"matchScore"`  // 0-100 percentage
    Strengths  []string `json:"strengths"`
    Weaknesses []string `json:"weaknesses"`
    Highlights []string `json:"highlights"`
    Feedback   string   `json:"feedback"`
}

type MatchResult struct {
    ID         int       `json:"id"`
    UserID     int       `json:"user_id"`
    JobID      int       `json:"job_id"`
    MatchScore int       `json:"match_score"`
    Strengths  []string  `json:"strengths"`
    Weaknesses []string  `json:"weaknesses"`
    Highlights []string  `json:"highlights"`
    Feedback   string    `json:"feedback"`
    CreatedAt  time.Time `json:"created_at"`
}

type QuotaCheckResult struct {
    Allowed bool   `json:"allowed"`
    Reason  string `json:"reason"`
    Status  QuotaStatus `json:"status"`
}

type QuotaStatus struct {
    Used  int `json:"used"`
    Limit int `json:"limit"` // -1 for unlimited
}

// Add timeout to prevent indefinite waiting on AI operations
// Job analysis is complex but should complete within 30 seconds
aiCtx, cancel := context.WithTimeout(ctx, 30*time.Second)
defer cancel()

response, err := j.model.Generate(aiCtx, llm.GenerateRequest{
    Prompt:       *prompt,
    ResponseType: llm.ResponseTypeMatchResult,
})

func (j *JobMatcherService) validateMatchResult(result *models.MatchResult) {
    // Ensure score is 0-100
    if result.MatchScore < 0 || result.MatchScore > 100 {
        result.MatchScore = 0
    }
    
    // Ensure arrays are never empty
    if len(result.Strengths) == 0 {
        result.Strengths = []string{"No specific strengths identified"}
    }
    
    if len(result.Weaknesses) == 0 {
        result.Weaknesses = []string{"No specific weaknesses identified"}
    }
    
    if len(result.Highlights) == 0 {
        result.Highlights = []string{"No specific highlights identified"}
    }
}