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This endpoint takes raw resume text and uses OpenAI (via OpenRouter) to extract structured JSON data according to a predefined schema. It’s typically used after parsing a PDF with the /api/parse-resume endpoint.

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Endpoint

POST /api/extract-info

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Request

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text
string
required
Raw resume text to parse. This is typically the text field returned from the /api/parse-resume endpoint.

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Response

The response is a structured resume object with the following fields:
​
personalInfo
object
Personal information and contact details
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personalInfo.name
string
Full name
​
personalInfo.title
string
Job title or professional headline
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personalInfo.location
string
City and state/country
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personalInfo.phone
string
Phone number
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personalInfo.email
string
Email address
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personalInfo.website
string
Personal website URL
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personalInfo.linkedin
string
LinkedIn profile URL
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personalInfo.github
string
GitHub profile URL
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summary
string
Professional summary or objective statement
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skills
object
Categorized list of skills
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skills.languages
array of strings
Programming languages
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skills.frameworksAndTools
array of strings
Frameworks, libraries, and development tools
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skills.libraries
array of strings
Specific libraries and packages
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skills.softSkills
array of strings
Soft skills and interpersonal abilities
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experience
array of objects
Work experience entries
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experience[].company
string
Company name
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experience[].position
string
Job title
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experience[].location
string
Job location
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experience[].startDate
string
Start date
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experience[].endDate
string
End date or “Present”
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experience[].isCurrentRole
boolean
Whether this is the current position
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experience[].description
array of strings
Bullet points describing responsibilities and achievements
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experience[].technologies
array of strings
Technologies used in this role
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projects
array of objects
Project entries
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projects[].name
string
Project name
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projects[].role
string
Role in the project
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projects[].startDate
string
Start date
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projects[].endDate
string
End date
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projects[].link
string or null
Project URL or repository link
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projects[].description
array of strings
Bullet points describing the project
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projects[].technologies
array of strings
Technologies used in the project
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education
array of objects
Education entries
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education[].university
string
Institution name
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education[].degree
string
Degree type (e.g., “Bachelor of Science”)
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education[].branch
string
Major or field of study
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education[].location
string
Institution location
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education[].sgpa
string
GPA or grade
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education[].startDate
string
Start date
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education[].endDate
string
End date or expected graduation
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extracurricular
array of strings
Extracurricular activities, awards, and achievements
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customSections
array of objects
Additional custom sections (e.g., certifications, languages)
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customSections[].title
string
Section title
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customSections[].items
array of strings
Items in this section

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Example

curl -X POST https://wrkks.vercel.app/api/extract-info \
  -H "Content-Type: application/json" \
  -d '{
    "text": "John Doe\nSoftware Engineer\[email protected]\n..."
  }'

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Response

{
  "personalInfo": {
    "name": "John Doe",
    "title": "Software Engineer",
    "location": "San Francisco, CA",
    "phone": "+1 (555) 123-4567",
    "email": "[email protected]",
    "website": "https://johndoe.com",
    "linkedin": "https://linkedin.com/in/johndoe",
    "github": "https://github.com/johndoe"
  },
  "summary": "Experienced software engineer with 5+ years building scalable web applications",
  "skills": {
    "languages": ["JavaScript", "TypeScript", "Python"],
    "frameworksAndTools": ["React", "Next.js", "Node.js"],
    "libraries": ["TailwindCSS", "Prisma"],
    "softSkills": ["Leadership", "Communication"]
  },
  "experience": [
    {
      "company": "Tech Corp",
      "position": "Senior Software Engineer",
      "location": "San Francisco, CA",
      "startDate": "Jan 2020",
      "endDate": "Present",
      "isCurrentRole": true,
      "description": [
        "Led development of customer-facing dashboard",
        "Improved page load times by 40%"
      ],
      "technologies": ["React", "TypeScript", "AWS"]
    }
  ],
  "projects": [],
  "education": [
    {
      "university": "State University",
      "degree": "Bachelor of Science",
      "branch": "Computer Science",
      "location": "Berkeley, CA",
      "sgpa": "3.8",
      "startDate": "2015",
      "endDate": "2019"
    }
  ],
  "extracurricular": [],
  "customSections": []
}

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Error responses

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500 Internal Server Error

Returned when AI extraction fails or returns invalid data: 
{
  "msg": "Failed to parse resume details"
}
Or with API error details: 
{
  "msg": "Failed to parse PDF",
  "details": "Rate limit exceeded"
}

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Implementation

The endpoint uses OpenAI’s chat completion API via OpenRouter with:
  • Model configured via OPENROUTER_MODEL_NAME environment variable
  • Temperature set to 0 for consistent extraction
  • JSON response format enforced
  • System prompt instructing the model to output only valid JSON
Source: /app/api/extract-info/route.ts:84-98

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