Generating Resume PDFs

POST /api/interview/resume/pdf/:interviewReportId

credentials: "include"

import { generateResumePdf } from './features/interview/services/interview.api'

async function downloadResume(interviewReportId) {
  try {
    // Get PDF blob
    const pdfBlob = await generateResumePdf({ interviewReportId })
    
    // Create download link
    const url = window.URL.createObjectURL(pdfBlob)
    const link = document.createElement('a')
    link.href = url
    link.download = `resume_${interviewReportId}.pdf`
    
    // Trigger download
    document.body.appendChild(link)
    link.click()
    
    // Cleanup
    document.body.removeChild(link)
    window.URL.revokeObjectURL(url)
    
  } catch (error) {
    if (error.response?.status === 404) {
      alert('Interview report not found')
    } else {
      alert('Failed to generate resume PDF')
    }
  }
}

export const generateResumePdf = async ({ interviewReportId }) => {
    const response = await api.post(
      `/api/interview/resume/pdf/${interviewReportId}`, 
      null, 
      {
        responseType: "blob"
      }
    )
    
    return response.data
}

async function generateResumePdfController(req, res) {
    const { interviewReportId } = req.params
    
    // 1. Fetch interview report
    const interviewReport = await interviewReportModel.findById(interviewReportId)
    
    if (!interviewReport) {
        return res.status(404).json({
            message: "Interview report not found."
        })
    }
    
    // 2. Extract required data
    const { resume, jobDescription, selfDescription } = interviewReport
    
    // 3. Generate PDF via AI service
    const pdfBuffer = await generateResumePdf({ 
      resume, 
      jobDescription, 
      selfDescription 
    })
    
    // 4. Set response headers
    res.set({
        "Content-Type": "application/pdf",
        "Content-Disposition": `attachment; filename=resume_${interviewReportId}.pdf`
    })
    
    // 5. Send PDF
    res.send(pdfBuffer)
}

async function generateResumePdf({ resume, selfDescription, jobDescription }) {
    
    // Define schema for AI response
    const resumePdfSchema = z.object({
        html: z.string().describe(
          "The HTML content of the resume which can be converted to PDF"
        )
    })
    
    // Create prompt
    const prompt = `Generate resume for a candidate with the following details:
                    Resume: ${resume}
                    Self Description: ${selfDescription}
                    Job Description: ${jobDescription}

                    The resume should be tailored for the given job description 
                    and should highlight the candidate's strengths and relevant experience.
                    The HTML content should be well-formatted and structured, 
                    making it easy to read and visually appealing.
                    The content should not sound like it's generated by AI.
                    The resume should ideally be 1-2 pages long when converted to PDF.
                    Focus on quality rather than quantity.`
    
    // Call AI
    const response = await ai.models.generateContent({
        model: "gemini-3-flash-preview",
        contents: prompt,
        config: {
            responseMimeType: "application/json",
            responseSchema: zodToJsonSchema(resumePdfSchema)
        }
    })
    
    // Parse response
    const jsonContent = JSON.parse(response.text)
    
    // Convert HTML to PDF
    const pdfBuffer = await generatePdfFromHtml(jsonContent.html)
    
    return pdfBuffer
}

const pdfBuffer = await page.pdf({
    format: "A4",      // Standard paper size
    margin: {
        top: "20mm",    // Professional margins
        bottom: "20mm",
        left: "15mm",
        right: "15mm"
    }
})

{
  "message": "Interview report not found."
}

credentials: "include"

import { 
  generateInterviewReport, 
  generateResumePdf 
} from './features/interview/services/interview.api'

async function completeWorkflow() {
  // Step 1: Generate interview report
  const reportResult = await generateInterviewReport({
    jobDescription: `
      Senior Software Engineer - Backend
      
      Requirements:
      - 5+ years Node.js experience
      - Microservices architecture
      - PostgreSQL and MongoDB
      - AWS deployment
    `,
    resumeFile: document.getElementById('resume').files[0],
    selfDescription: `
      Senior backend engineer with 7 years building scalable APIs.
      Led migration from monolith to microservices at previous company.
      Deep experience with Node.js, Express, and database optimization.
    `,
    title: "Senior Software Engineer - Backend"
  })
  
  const reportId = reportResult.interviewReport._id
  console.log('Interview report created:', reportId)
  console.log('Match score:', reportResult.interviewReport.matchScore)
  
  // Step 2: Generate tailored resume PDF
  const pdfBlob = await generateResumePdf({ 
    interviewReportId: reportId 
  })
  
  // Step 3: Download PDF
  const url = window.URL.createObjectURL(pdfBlob)
  const link = document.createElement('a')
  link.href = url
  link.download = `resume_backend_engineer.pdf`
  document.body.appendChild(link)
  link.click()
  document.body.removeChild(link)
  window.URL.revokeObjectURL(url)
  
  console.log('Resume PDF downloaded successfully')
}

import { useState } from 'react'
import { generateResumePdf } from '../services/interview.api'

function ResumePdfButton({ interviewReportId }) {
  const [loading, setLoading] = useState(false)
  const [error, setError] = useState(null)
  
  const handleDownload = async () => {
    setLoading(true)
    setError(null)
    
    try {
      const pdfBlob = await generateResumePdf({ interviewReportId })
      
      const url = window.URL.createObjectURL(pdfBlob)
      const link = document.createElement('a')
      link.href = url
      link.download = `tailored_resume_${interviewReportId}.pdf`
      document.body.appendChild(link)
      link.click()
      document.body.removeChild(link)
      window.URL.revokeObjectURL(url)
      
    } catch (err) {
      setError(err.response?.data?.message || 'Failed to generate PDF')
    } finally {
      setLoading(false)
    }
  }
  
  return (
    <div>
      <button 
        onClick={handleDownload} 
        disabled={loading}
      >
        {loading ? 'Generating PDF...' : 'Download Tailored Resume'}
      </button>
      {error && <p className="error">{error}</p>}
    </div>
  )
}