Resume

The Java SDK supports the Mindee V1 Resume API.

Product Specifications

Specification

Details

Endpoint Name

resume

Recommended Version

v1.2

Supports Polling/Webhooks

✔️ Yes

Support Synchronous HTTP Calls

❌ No

Geography

🌐 Global

Quick-Start

Using the sample below, we are going to illustrate how to extract the data that we want using the SDK.

Sample Code

import com.mindee.MindeeClient;
import com.mindee.input.LocalInputSource;
import com.mindee.parsing.common.AsyncPredictResponse;
import com.mindee.product.resume.ResumeV1;
import java.io.File;
import java.io.IOException;

public class SimpleMindeeClient {

  public static void main(String[] args) throws IOException, InterruptedException {
    String apiKey = "my-api-key";
    String filePath = "/path/to/the/file.ext";

    // Init a new client
    MindeeClient mindeeClient = new MindeeClient(apiKey);

    // Load a file from disk
    LocalInputSource inputSource = new LocalInputSource(new File(filePath));

    // Parse the file asynchronously
    AsyncPredictResponse<ResumeV1> response = mindeeClient.enqueueAndParse(
        ResumeV1.class,
        inputSource
    );

    // Print a summary of the response
    System.out.println(response.toString());

    // Print a summary of the predictions
//  System.out.println(response.getDocumentObj().toString());

    // Print the document-level predictions
//    System.out.println(response.getDocumentObj().getInference().getPrediction().toString());

    // Print the page-level predictions
//    response.getDocumentObj().getInference().getPages().forEach(
//        page -> System.out.println(page.toString())
//    );
  }

}

Sample Output (rST)

########
Document
########
:Mindee ID: 9daa3085-152c-454e-9245-636f13fc9dc3
:Filename: default_sample.jpg

Inference
#########
:Product: mindee/resume v1.1
:Rotation applied: Yes

Prediction
==========
:Document Language: ENG
:Document Type: RESUME
:Given Names: Christopher
:Surnames: Morgan
:Nationality:
:Email Address: [email protected]
:Phone Number: +44 (0)20 7666 8555
:Address: 177 Great Portland Street, London, W5W 6PQ
:Social Networks:
  +----------------------+----------------------------------------------------+
  | Name                 | URL                                                |
  +======================+====================================================+
  | LinkedIn             | linkedin.com/christopher.morgan                    |
  +----------------------+----------------------------------------------------+
:Profession: Senior Web Developer
:Job Applied:
:Languages:
  +----------+----------------------+
  | Language | Level                |
  +==========+======================+
  | SPA      | Fluent               |
  +----------+----------------------+
  | ZHO      | Beginner             |
  +----------+----------------------+
  | DEU      | Beginner             |
  +----------+----------------------+
:Hard Skills: HTML5
              PHP OOP
              JavaScript
              CSS
              MySQL
              SQL
:Soft Skills: Project management
              Creative design
              Strong decision maker
              Innovative
              Complex problem solver
              Service-focused
:Education:
  +-----------------+---------------------------+-----------+----------+---------------------------+-------------+------------+
  | Domain          | Degree                    | End Month | End Year | School                    | Start Month | Start Year |
  +=================+===========================+===========+==========+===========================+=============+============+
  | Computer Inf... | Bachelor                  |           | 2014     | Columbia University, NY   |             |            |
  +-----------------+---------------------------+-----------+----------+---------------------------+-------------+------------+
:Professional Experiences:
  +-----------------+------------+--------------------------------------+---------------------------+-----------+----------+----------------------+-------------+------------+
  | Contract Type   | Department | Description                          | Employer                  | End Month | End Year | Role                 | Start Month | Start Year |
  +=================+============+======================================+===========================+===========+==========+======================+=============+============+
  |                 |            | Cooperate with designers to creat... | Luna Web Design, New York | 05        | 2019     | Web Developer        | 09          | 2015       |
  +-----------------+------------+--------------------------------------+---------------------------+-----------+----------+----------------------+-------------+------------+
:Certificates:
  +------------+--------------------------------+---------------------------+------+
  | Grade      | Name                           | Provider                  | Year |
  +============+================================+===========================+======+
  |            | PHP Framework (certificate)... |                           |      |
  +------------+--------------------------------+---------------------------+------+

Field Types

Standard Fields

These fields are generic and used in several products.

BaseField

Each prediction object contains a set of fields that inherit from the generic BaseField class. A typical BaseField object will have the following attributes:

confidence (Double): the confidence score of the field prediction.
boundingBox (Polygon): contains exactly 4 relative vertices (points) coordinates of a right rectangle containing the field in the document.
polygon (Polygon): contains the relative vertices coordinates (polygon extends List<Point>) of a polygon containing the field in the image.
pageId (Integer): the ID of the page, always null when at document-level.

A Point simply refers to a List of Double.

Aside from the previous attributes, all basic fields have access to a custom toString method that can be used to print their value as a string.

ClassificationField

The classification field ClassificationField extends BaseField, but also implements:

value (strong): corresponds to the field value.
confidence (double): the confidence score of the field prediction.

A classification field's value is always a String.

StringField

The text field StringField extends BaseField, but also implements:

value (String): corresponds to the field value.
rawValue (String): corresponds to the raw value as it appears on the document.

Specific Fields

Fields which are specific to this product; they are not used in any other product.

Certificates Field

The list of certificates obtained by the candidate.

A ResumeV1Certificate implements the following attributes:

grade (String): The grade obtained for the certificate.
name (String): The name of certification.
provider (String): The organization or institution that issued the certificate.
year (String): The year when a certificate was issued or received. Fields which are specific to this product; they are not used in any other product.

Education Field

The list of the candidate's educational background.

A ResumeV1Education implements the following attributes:

degreeDomain (String): The area of study or specialization.
degreeType (String): The type of degree obtained, such as Bachelor's, Master's, or Doctorate.
endMonth (String): The month when the education program or course was completed.
endYear (String): The year when the education program or course was completed.
school (String): The name of the school.
startMonth (String): The month when the education program or course began.
startYear (String): The year when the education program or course began. Fields which are specific to this product; they are not used in any other product.

Languages Field

The list of languages that the candidate is proficient in.

A ResumeV1Language implements the following attributes:

language (String): The language's ISO 639 code.
level (String): The candidate's level for the language. Possible values include:
- Native
- Fluent
- Proficient
- Intermediate
- Beginner

Fields which are specific to this product; they are not used in any other product.

Professional Experiences Field

The list of the candidate's professional experiences.

A ResumeV1ProfessionalExperience implements the following attributes:

contractType (String): The type of contract for the professional experience. Possible values include:
- Full-Time
- Part-Time
- Internship
- Freelance
department (String): The specific department or division within the company.
description (String): The description of the professional experience as written in the document.
employer (String): The name of the company or organization.
endMonth (String): The month when the professional experience ended.
endYear (String): The year when the professional experience ended.
role (String): The position or job title held by the candidate.
startMonth (String): The month when the professional experience began.
startYear (String): The year when the professional experience began. Fields which are specific to this product; they are not used in any other product.

The list of social network profiles of the candidate.

A ResumeV1SocialNetworksUrl implements the following attributes:

name (String): The name of the social network.
url (String): The URL of the social network.

Attributes

The following fields are extracted for Resume V1:

Address

address: The location information of the candidate, including city, state, and country.

System.out.println(
  result.getDocument().getInference().getPrediction().getAddress().value
);

Certificates

certificates(List<ResumeV1Certificate>): The list of certificates obtained by the candidate.

for (certificatesElem : result.getDocument().getInference().getPrediction().getCertificates())
{
    System.out.println(certificatesElem.value);
}

Document Language

documentLanguage: The ISO 639 code of the language in which the document is written.

System.out.println(
  result.getDocument().getInference().getPrediction().getDocumentLanguage().value
);

Document Type

documentType: The type of the document sent.

Possible values include:

'RESUME'
'MOTIVATION_LETTER'
'RECOMMENDATION_LETTER'

System.out.println(
  result.getDocument().getInference().getPrediction().getDocumentType().value
);

Education

education(List<ResumeV1Education>): The list of the candidate's educational background.

for (educationElem : result.getDocument().getInference().getPrediction().getEducation())
{
    System.out.println(educationElem.value);
}

Email Address

emailAddress: The email address of the candidate.

System.out.println(
  result.getDocument().getInference().getPrediction().getEmailAddress().value
);

Given Names

givenNames: The candidate's first or given names.

for (givenNamesElem : result.getDocument().getInference().getPrediction().getGivenNames())
{
    System.out.println(givenNamesElem.value);
}

Hard Skills

hardSkills: The list of the candidate's technical abilities and knowledge.

for (hardSkillsElem : result.getDocument().getInference().getPrediction().getHardSkills())
{
    System.out.println(hardSkillsElem.value);
}

Job Applied

jobApplied: The position that the candidate is applying for.

System.out.println(
  result.getDocument().getInference().getPrediction().getJobApplied().value
);

Languages

languages(List<ResumeV1Language>): The list of languages that the candidate is proficient in.

for (languagesElem : result.getDocument().getInference().getPrediction().getLanguages())
{
    System.out.println(languagesElem.value);
}

Nationality

nationality: The ISO 3166 code for the country of citizenship of the candidate.

System.out.println(
  result.getDocument().getInference().getPrediction().getNationality().value
);

Phone Number

phoneNumber: The phone number of the candidate.

System.out.println(
  result.getDocument().getInference().getPrediction().getPhoneNumber().value
);

Profession

profession: The candidate's current profession.

System.out.println(
  result.getDocument().getInference().getPrediction().getProfession().value
);

Professional Experiences

professionalExperiences(List<ResumeV1ProfessionalExperience>): The list of the candidate's professional experiences.

for (professionalExperiencesElem : result.getDocument().getInference().getPrediction().getProfessionalExperiences())
{
    System.out.println(professionalExperiencesElem.value);
}

socialNetworksUrls(List<ResumeV1SocialNetworksUrl>): The list of social network profiles of the candidate.

for (socialNetworksUrlsElem : result.getDocument().getInference().getPrediction().getSocialNetworksUrls())
{
    System.out.println(socialNetworksUrlsElem.value);
}

Soft Skills

softSkills: The list of the candidate's interpersonal and communication abilities.

for (softSkillsElem : result.getDocument().getInference().getPrediction().getSoftSkills())
{
    System.out.println(softSkillsElem.value);
}

Surnames

surnames: The candidate's last names.

for (surnamesElem : result.getDocument().getInference().getPrediction().getSurnames())
{
    System.out.println(surnamesElem.value);
}

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