inda_hr.ResumeParsingApi

All URIs are relative to https://api.inda.ai

Method	HTTP request	Description
anonymize_cv_post	POST /hr/v2/parse/resume/anonymize/	Anonymize CV
bulk_map_entity_post	POST /hr/v2/keywords/bulk/map/entity/	Bulk Map Entity
map_entity_post	POST /hr/v2/keywords/map/entity/	Map Entity
parse_resume_post	POST /hr/v2/parse/resume/data/	Parse Resume
text_extraction_post	POST /hr/v2/parse/resume/text/	Text Extraction

anonymize_cv_post

DocumentAnonymizationResponse anonymize_cv_post(base_file_doc)

Anonymize CV

This method allows you to anonymize a CV/resume (only textual documents, not scanned documents or images) by covering the main sensitive information in the document. Output is always a PDF file containing an anonymized copy of the source document. Masked entities are: given name, family name, birthdate, telephone numbers, emails, links, gender, nationality, profile picture. Supported extensions: pdf, doc, docx, odt, txt, html, pptx, rtf.

Example

Bearer Authentication (APIKey):

import time
import inda_hr
from inda_hr.api import resume_parsing_api
from inda_hr.model.document_anonymization_response import DocumentAnonymizationResponse
from inda_hr.model.error_model import ErrorModel
from inda_hr.model.base_file_doc import BaseFileDoc
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
    host = "https://api.inda.ai"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
    access_token = 'YOUR_BEARER_TOKEN'
)

# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = resume_parsing_api.ResumeParsingApi(api_client)
    base_file_doc = BaseFileDoc(
        file=open('/path/to/file', 'rb'),
        file_ext="file_ext_example",
    ) # BaseFileDoc | 
    src_lang = "it" # str | Language to use to interpret the text. If missing, language detection is performed. (optional)

    # example passing only required values which don't have defaults set
    try:
        # Anonymize CV
        api_response = api_instance.anonymize_cv_post(base_file_doc)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->anonymize_cv_post: %s\n" % e)

    # example passing only required values which don't have defaults set
    # and optional values
    try:
        # Anonymize CV
        api_response = api_instance.anonymize_cv_post(base_file_doc, src_lang=src_lang)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->anonymize_cv_post: %s\n" % e)

Parameters

Name	Type	Description	Notes
base_file_doc	BaseFileDoc
src_lang	str	Language to use to interpret the text. If missing, language detection is performed.	[optional]

Return type

DocumentAnonymizationResponse

Authorization

APIKey

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Document Successfully Processed	-
422	Unprocessable Entity	-
415	Unsupported Media Type	-
500	Internal Server Error	-
503	Service Unavailable	-
400	Bad Request	-

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bulk_map_entity_post

MultiEntityMapping bulk_map_entity_post(multi_entity_input)

Bulk Map Entity

This method wraps the Map Entity method and allows a user to send all the entities to be mapped in one API call, e.g., for pagination purposes. Note that the request does not raise any Validation Error on the input data but instead it returns all the errors in the response.

Example

Bearer Authentication (APIKey):

import time
import inda_hr
from inda_hr.api import resume_parsing_api
from inda_hr.model.multi_entity_mapping import MultiEntityMapping
from inda_hr.model.http_validation_error import HTTPValidationError
from inda_hr.model.multi_entity_input import MultiEntityInput
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
    host = "https://api.inda.ai"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
    access_token = 'YOUR_BEARER_TOKEN'
)

# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = resume_parsing_api.ResumeParsingApi(api_client)
    multi_entity_input = MultiEntityInput(
        entities=[
            IdEntityInput(
                entity_id="entity_id_example",
                entity=EntityInput(
                    input_language="it",
                    output_language="it",
                    entity_type="entity_type_example",
                    allowed_outputs=[
                        AllowedOutput(
                            id="id_example",
                            value="value_example",
                        ),
                    ],
                    input_string="input_string_example",
                    severity=0.5,
                ),
            ),
        ],
    ) # MultiEntityInput | 

    # example passing only required values which don't have defaults set
    try:
        # Bulk Map Entity
        api_response = api_instance.bulk_map_entity_post(multi_entity_input)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->bulk_map_entity_post: %s\n" % e)

Parameters

Name	Type	Description	Notes
multi_entity_input	MultiEntityInput

Return type

MultiEntityMapping

Authorization

APIKey

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Entities Successfully Mapped	-
422	Validation Error	-

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map_entity_post

EntityMapping map_entity_post(entity_input)

Map Entity

This method maps an input string (ideally an entity extracted with the Parse Resume method) to the most similar string among a list of strings chosen by the user (AllowedOutputs). Note that, after a best match has been identified, it is actually presented as output only when it passes a similarity check, which takes into account the similarity of this best match with the input string, but also the similarity of the other elements of allowed outputs with the input string (namely, if many allowed outputs have a comparable similarity level, the similarity check is not passed, because there is not a clear winner). When the severity check is passed, the id of the best match is given in output (see the payload and response examples on the right); otherwise, an empty string is returned instead of the id. The severity of the similarity check can be controlled via the severity parameter, which takes value between 0 and 1: a user who prefers to obtain the best match also when there is not guarantee it actually corresponds to the input string should set severity to a low value (i.e., close to 0); vice versa, a user who prefers to have a response only when there is a high confidence in the correspondence should set severity to a large value (i.e., close to 1); an intermediate value (such as the default value 0.5) is appropriate in many situations. The method has been specialized for different entity types, and for each of them it performs an analysis optimized over the specific type. The currently supported entity types are Data.EducationExperiences.Organization.OrganizationName and Data.EducationExperiences.EducationTitle. If the entity type is a string that does not match any of the supported entity types, the mapping is performed using a non-specialized method.

Example

Bearer Authentication (APIKey):

import time
import inda_hr
from inda_hr.api import resume_parsing_api
from inda_hr.model.error_model import ErrorModel
from inda_hr.model.entity_input import EntityInput
from inda_hr.model.entity_mapping import EntityMapping
from inda_hr.model.http_validation_error import HTTPValidationError
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
    host = "https://api.inda.ai"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
    access_token = 'YOUR_BEARER_TOKEN'
)

# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = resume_parsing_api.ResumeParsingApi(api_client)
    entity_input = EntityInput(
        input_language="it",
        output_language="it",
        entity_type="entity_type_example",
        allowed_outputs=[
            AllowedOutput(
                id="id_example",
                value="value_example",
            ),
        ],
        input_string="input_string_example",
        severity=0.5,
    ) # EntityInput | 

    # example passing only required values which don't have defaults set
    try:
        # Map Entity
        api_response = api_instance.map_entity_post(entity_input)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->map_entity_post: %s\n" % e)

Parameters

Name	Type	Description	Notes
entity_input	EntityInput

Return type

EntityMapping

Authorization

APIKey

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Entity Successfully Mapped	-
400	Bad Request	-
422	Validation Error	-

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parse_resume_post

ExtractionItem parse_resume_post(base_file)

Parse Resume

This method performs the Information Extraction from a resume, i.e., it recognizes the named entities contained in a given resume and reconstructs the relations between them, returning a structured information in the form of a json file. The method requires in input the binary and the extension of the file and automatically performs many steps: (i) Document Layout Analysis, (ii) Optical Character Recognition (if the input document is an image), (iii) Text Extraction, (iv) Named Entity Recognition, (v) Relation Extraction, and, finally, (vi) Face Recognition (which is carried out to identify, if present, the candidate photo). The information provided in the output (see the schema below and the example on the right) can be used as structured data input for the Add Resume method (some adjustments may be required). The allowed file extensions are pdf, doc, docx, odt, txt, html, pptx, rtf, jpg, jpeg, png, tif, tiff . Please consider to use the Info Extraction Feedback to inform us about differences between user's expectations and the actual data provided as output by INDA engine. It is very useful to improve our algorithms' performances.

Example

Bearer Authentication (APIKey):

import time
import inda_hr
from inda_hr.api import resume_parsing_api
from inda_hr.model.extraction_item import ExtractionItem
from inda_hr.model.error_model import ErrorModel
from inda_hr.model.base_file import BaseFile
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
    host = "https://api.inda.ai"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
    access_token = 'YOUR_BEARER_TOKEN'
)

# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = resume_parsing_api.ResumeParsingApi(api_client)
    base_file = BaseFile(
        file=open('/path/to/file', 'rb'),
        file_ext="file_ext_example",
    ) # BaseFile | 
    src_lang = "it" # str | Optional. Language to use to extract data from the *Attachment.CV.File*.If missing, the detected language from the input file text is assumed as `src_lang`. (optional)
    dst_lang = "dst_lang_example" # str | Optional. Destination language in which the following *Data* entities are translated: *Skills*, *WorkExperiences.Skills*, *JobTitles*, *WorkExperiences.PositionTitle* and *Languages*.If missing, the input or detected `src_lang` is assumed as `dst_lang`. (optional)
    graphics = False # bool | Whether to read skill graphs such as bars, pie charts, and symbols. (optional) if omitted the server will use the default value of False

    # example passing only required values which don't have defaults set
    try:
        # Parse Resume
        api_response = api_instance.parse_resume_post(base_file)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->parse_resume_post: %s\n" % e)

    # example passing only required values which don't have defaults set
    # and optional values
    try:
        # Parse Resume
        api_response = api_instance.parse_resume_post(base_file, src_lang=src_lang, dst_lang=dst_lang, graphics=graphics)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->parse_resume_post: %s\n" % e)

Parameters

Name	Type	Description	Notes
base_file	BaseFile
src_lang	str	Optional. Language to use to extract data from the Attachment.CV.File.If missing, the detected language from the input file text is assumed as `src_lang`.	[optional]
dst_lang	str	Optional. Destination language in which the following Data entities are translated: Skills, WorkExperiences.Skills, JobTitles, WorkExperiences.PositionTitle and Languages.If missing, the input or detected `src_lang` is assumed as `dst_lang`.	[optional]
graphics	bool	Whether to read skill graphs such as bars, pie charts, and symbols.	[optional] if omitted the server will use the default value of False

Return type

ExtractionItem

Authorization

APIKey

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Document Successfully Processed	-
422	Unprocessable Entity	-
415	Unsupported Media Type	-
500	Internal Server Error	-
503	Service Unavailable	-
400	Bad Request	-

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text_extraction_post

TextResponse text_extraction_post(base_file)

Text Extraction

This method extracts the text from a resume by performing the first steps of Parse Resume. In particular, the method requires in input the binary and the extension of the file and automatically performs (i) Document Layout Analysis, (ii) Optical Character Recognition (if the input document is an image), and (iii) Text Extraction. The allowed file extensions are pdf, doc, docx, odt, txt, html, pptx, rtf, jpg, jpeg, png, tif, tiff .

Example

Bearer Authentication (APIKey):

import time
import inda_hr
from inda_hr.api import resume_parsing_api
from inda_hr.model.text_response import TextResponse
from inda_hr.model.error_model import ErrorModel
from inda_hr.model.base_file import BaseFile
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
    host = "https://api.inda.ai"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
    access_token = 'YOUR_BEARER_TOKEN'
)

# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = resume_parsing_api.ResumeParsingApi(api_client)
    base_file = BaseFile(
        file=open('/path/to/file', 'rb'),
        file_ext="file_ext_example",
    ) # BaseFile | 

    # example passing only required values which don't have defaults set
    try:
        # Text Extraction
        api_response = api_instance.text_extraction_post(base_file)
        pprint(api_response)
    except inda_hr.ApiException as e:
        print("Exception when calling ResumeParsingApi->text_extraction_post: %s\n" % e)

Parameters

Name	Type	Description	Notes
base_file	BaseFile

Return type

TextResponse

Authorization

APIKey

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Successfully Parsed Text	-
422	Unprocessable Entity	-
415	Unsupported Media Type	-

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inda_hr.ResumeParsingApi

anonymize_cv_post

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

bulk_map_entity_post

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

map_entity_post

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

parse_resume_post

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

text_extraction_post

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details