The Ruby Client Library supports the Resume API.

📝
Product Specs

Specification Details
Endpoint Name resume
Recommended Version v1.2
Supports Polling/Webhooks ✔️ Yes
Support Synchronous HTTP Calls ❌ No
Geography 🌐 Global

Specification	Details
Endpoint Name	`resume`
Recommended Version	`v1.2`
Supports Polling/Webhooks	✔️ Yes
Support Synchronous HTTP Calls	❌ No
Geography	🌐 Global

🔐
Polling Limitations

Setting Parameter name Default Value
Initial Delay Before Polling initial_delay_seconds 2 seconds
Default Delay Between Calls delay_sec 1.5 seconds
Polling Attempts Before Timeout max_retries 80 retries

Setting	Parameter name	Default Value
Initial Delay Before Polling	`initial_delay_seconds`	2 seconds
Default Delay Between Calls	`delay_sec`	1.5 seconds
Polling Attempts Before Timeout	`max_retries`	80 retries

Using the sample below,
we are going to illustrate how to extract the data that we want using the Ruby Client Library.
Resume sample

Quick-Start

#
# Install the Ruby client library by running:
# gem install mindee
#

require 'mindee'

# Init a new client
mindee_client = Mindee::Client.new(api_key: 'my-api-key')

# Load a file from disk
input_source = mindee_client.source_from_path('/path/to/the/file.ext')

# Parse the file
result = mindee_client.parse(
  input_source,
  Mindee::Product::Resume::ResumeV1
)

# Print a full summary of the parsed data in RST format
puts result.document

# Print the document-level parsed data
# puts result.document.inference.prediction

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.

Basic Field

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

value (String, Float, Integer, bool): corresponds to the field value. Can be nil if no value was extracted.
confidence (Float, nil): the confidence score of the field prediction.
bounding_box (Mindee::Geometry::Quadrilateral, nil): contains exactly 4 relative vertices (points) coordinates of a right rectangle containing the field in the document.
polygon (Mindee::Geometry::Polygon, nil): contains the relative vertices coordinates (Point) of a polygon containing the field in the image.
page_id (Integer, nil): the ID of the page, always nil when at document-level.
reconstructed (bool): indicates whether an object was reconstructed (not extracted as the API gave it).

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

Classification Field

The classification field ClassificationField does not implement all the basic Field attributes. It only implements
value, confidence and page_id.

Note: a classification field's value is always a String`.

String Field

The text field StringField only has one constraint: it's value is a String (or nil).

Specific Fields

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

Social Networks Field

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.
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.

Education Field

The list of the candidate's educational background.

A ResumeV1Education implements the following attributes:

degree_domain (String): The area of study or specialization.
degree_type (String): The type of degree obtained, such as Bachelor's, Master's, or Doctorate.
end_month (String): The month when the education program or course was completed.
end_year (String): The year when the education program or course was completed.
school (String): The name of the school.
start_month (String): The month when the education program or course began.
start_year (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.

Professional Experiences Field

The list of the candidate's professional experiences.

A ResumeV1ProfessionalExperience implements the following attributes:

contract_type (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.
end_month (String): The month when the professional experience ended.
end_year (String): The year when the professional experience ended.
role (String): The position or job title held by the candidate.
start_month (String): The month when the professional experience began.
start_year (String): The year when the professional experience began.
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.

Attributes

The following fields are extracted for Resume V1:

Address

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

puts result.document.inference.prediction.address.value

Certificates

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

result.document.inference.prediction.certificates do |certificates_elem|
  puts certificates_elem.value
end

Document Language

document_language (StringField): The ISO 639 code of the language in which the document is written.

puts result.document.inference.prediction.document_language.value

Document Type

document_type (ClassificationField): The type of the document sent.

Possible values include:

RESUME
MOTIVATION_LETTER
RECOMMENDATION_LETTER

puts result.document.inference.prediction.document_type.value

Education

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

result.document.inference.prediction.education do |education_elem|
  puts education_elem.value
end

Email Address

email_address (StringField): The email address of the candidate.

puts result.document.inference.prediction.email_address.value

Given Names

given_names (Array<StringField>): The candidate's first or given names.

result.document.inference.prediction.given_names do |given_names_elem|
  puts given_names_elem.value
end

Hard Skills

hard_skills (Array<StringField>): The list of the candidate's technical abilities and knowledge.

result.document.inference.prediction.hard_skills do |hard_skills_elem|
  puts hard_skills_elem.value
end

Job Applied

job_applied (StringField): The position that the candidate is applying for.

puts result.document.inference.prediction.job_applied.value

Languages

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

result.document.inference.prediction.languages do |languages_elem|
  puts languages_elem.value
end

Nationality

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

puts result.document.inference.prediction.nationality.value

Phone Number

phone_number (StringField): The phone number of the candidate.

puts result.document.inference.prediction.phone_number.value

Profession

profession (StringField): The candidate's current profession.

puts result.document.inference.prediction.profession.value

Professional Experiences

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

result.document.inference.prediction.professional_experiences do |professional_experiences_elem|
  puts professional_experiences_elem.value
end

Social Networks

social_networks_urls (Array<ResumeV1SocialNetworksUrl>): The list of social network profiles of the candidate.

result.document.inference.prediction.social_networks_urls do |social_networks_urls_elem|
  puts social_networks_urls_elem.value
end

Soft Skills

soft_skills (Array<StringField>): The list of the candidate's interpersonal and communication abilities.

result.document.inference.prediction.soft_skills do |soft_skills_elem|
  puts soft_skills_elem.value
end

Surnames

surnames (Array<StringField>): The candidate's last names.

result.document.inference.prediction.surnames do |surnames_elem|
  puts surnames_elem.value
end

Questions?

Join our Slack

Resume

📝
Product Specs

🔐
Polling Limitations

Quick-Start

Field Types

Standard Fields

Basic Field

Classification Field

String Field

Specific Fields

Social Networks Field

Languages Field

Possible values include:

Education Field

Professional Experiences Field

Possible values include:

Certificates Field

Attributes

Address

Certificates

Document Language

Document Type

Possible values include:

Education

Email Address

Given Names

Hard Skills

Job Applied

Languages

Nationality

Phone Number

Profession

Professional Experiences

Social Networks

Soft Skills

Surnames

Questions?

📝Product Specs

🔐Polling Limitations

Quick-Start

Field Types

Standard Fields

Basic Field

Classification Field

String Field

Specific Fields

Social Networks Field

Languages Field

Possible values include:

Education Field

Professional Experiences Field

Possible values include:

Certificates Field

Attributes

Address

Certificates

Document Language

Document Type

Possible values include:

Education

Email Address

Given Names

Hard Skills

Job Applied

Languages

Nationality

Phone Number

Profession

Professional Experiences

Social Networks

Soft Skills

Surnames

Questions?

📝
Product Specs

🔐
Polling Limitations