SIKAI provides production-ready resume parsing and resume intelligence APIs for HR technology, recruiting, and executive-search products. Our services turn unstructured hiring data into reliable structured information, helping teams improve processing efficiency and reduce operational costs.
About us
Our team has published research at international data-science conferences, with work referenced by Wikipedia and indexed by SCI and IEEE. We specialize in multilingual resume parsing, semantic talent search, and intelligent candidate-job matching.
We continuously apply current research to practical recruiting workflows and support customers worldwide from teams in China and the United States.
Service introduction
Every open role may receive hundreds of applications. Recruiting teams need accurate candidate data and fast screening workflows to avoid missing qualified people or spending time on poor matches.
SIKAI's resume parsing, talent search, and matching APIs help recruiting systems ingest, store, analyze, and retrieve candidate data efficiently.
We support two deployment models:
Private deployment: Run SIKAI services on your own on-premises or cloud infrastructure.
SaaS: Call SIKAI's hosted APIs without managing service infrastructure.
Plan Information
Interface description
Get package information
The user package information returned includes the remaining resume parsing quota and package expiration time.
Send the base64-encoded resume file and return the parsing results. The new version 2.6.0 or above supports multiple analysis modes, including extreme speed mode, normal mode and high-precision mode.
Extreme Speed Mode: Suitable for users who have extremely high requirements for parsing speed. The parsing speed of a single resume is 3 times faster than the normal mode on average, and the parsing speed is significantly ahead of the industry standard. Currently, only pure Chinese or pure English resumes are supported, and mixed Chinese and English resumes will be processed as pure Chinese.
Normal Mode: Suitable for most purposes, the field integrity will be slightly higher than the extreme speed mode, and the parsing effect is significantly ahead of the industry standard.
High Precision Mode: Suitable for users who have extremely high requirements for parsing effects but are not too sensitive to parsing time. Combining the most advanced deep learning semantic understanding technology and a massive knowledge vocabulary, the most accurate analysis results in the industry are obtained.
Whether to return the original resume content, 1 returns, 0 does not return
handle_image
Int
No
Whether to process image resumes, 1 will process it, 0 will not process it
avatar
Int
No
Whether to extract resume avatar, 1 will be processed, 0 will not be processed
parse_mode
String
No
SIKAI's original parsing mode, customers can choose the most suitable resume parsing mode according to specific needs, fast extreme speed mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_mode
String
No
Image to text OCR mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_service
String
No
OCR service provider, tencent Tencent OCR, xiaoxi SIKAI self-developed OCR, alicloud Alibaba OCR, baidu Baidu OCR, the default is Baidu OCR (local deployment only)
Request content description (body)
Parameter
Parameter type
Required
Description
resume_base
String
Yes
Base64 encoded resume file content
file_name
String
Yes
Resume file name (please make sure the suffix is correct)
Please refer to Error code summary, if the parsing is successful, it will be 0
Int
errormessage
Error message
Parsing error message
String
version
Version
Resume parsing version
String
cv_language
Resume language
zh, zh/en, en
String
src_site
Resume source
51job, lagou, liepin, zhilian, other
String
src_id
Resume ID
The resume ID corresponding to the recruitment website. If the source of the resume is not identified, the ID will be empty
String
updated_time
Update time
Resume update time, empty if not
String
avatar_data
Resume avatar picture
Resume avatar picture in BASE64 format. If there is no avatar, an empty string will be returned
String
avatar_url
The URL where the resume avatar picture is located
If the avatar picture in the resume is in the form of a link, save the link URL where the avatar is located. If there is no link, an empty string will be returned
Resume integrity score, the resume content is approximately complete, the higher the score, the score range is 0-1
Double
Note: The fields returned by Chinese (parsing_result) and English (english_parsing_result) parsing are the same. Please refer to the returned parsing result list.
This API is only available for local deployment. Send the original resume file and return the parsed results. The new version 2.6.0 or above supports multiple analysis modes, including extreme speed mode, normal mode and high-precision mode.
Extreme Speed Mode: Suitable for users who have extremely high requirements for parsing speed. The parsing speed of a single resume is 3 times faster than the normal mode on average, and the parsing speed is significantly ahead of the industry standard. Currently, only pure Chinese or pure English resumes are supported, and mixed Chinese and English resumes will be processed as pure Chinese.
Normal Mode: Suitable for most purposes, the field integrity will be slightly higher than the extreme speed mode, and the parsing effect is significantly ahead of the industry standard.
High Precision Mode: Suitable for users who have extremely high requirements for parsing effects but are not too sensitive to parsing time. Combining the most advanced deep learning semantic understanding technology and a massive knowledge vocabulary, the most accurate analysis results in the industry are obtained.
Whether to return the original resume content, 1 returns, 0 does not return
handle_image
Int
No
Whether to process image resumes, 1 will process it, 0 will not process it
avatar
Int
No
Whether to extract resume avatar, 1 will be processed, 0 will not be processed (local deployment only)
parse_mode
String
No
SIKAI's original parsing mode, customers can choose the most suitable resume parsing mode according to specific needs, fast extreme speed mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_mode
String
No
Image to text OCR mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_service
String
No
OCR service provider, tencent Tencent OCR, xiaoxi SIKAI self-developed OCR, alicloud Alibaba OCR, baidu Baidu OCR, the default is Baidu OCR (local deployment only)
Request content description (body)
Parameter
Parameter type
Required
Description
file
File
Yes
Original resume file
Example of request content structure:
{"file":{原始简历},}
Return result description
Variable name
Variable meaning
Remarks
Field type
cv_name
Resume file name
System cache file name
String
cv_id
Resume ID
System cached resume ID
String
errorcode
Error code
Please refer to Error code summary, if the parsing is successful, it will be 0
Int
errormessage
Error message
Parsing error message
String
version
Version
Resume parsing version
String
cv_language
Resume language
zh, zh/en, en
String
src_site
Resume source
zhilian, 51job, liepin, lagou
String
avatar_data
Resume avatar picture
Resume avatar picture in BASE64 format. If there is no avatar, an empty string will be returned
String
avatar_url
The URL where the resume avatar picture is located
If the avatar picture in the resume is in the form of a link, save the link URL where the avatar is located. If there is no link, an empty string will be returned
Resume integrity score, the resume content is approximately complete, the higher the score, the score range is 0-1
Double
Note: The fields returned by Chinese (parsing_result) and English (english_parsing_result) parsing are the same. Please refer to the returned parsing result list.
The basic information variable name is basic_info and the variable type is object
Variable name
Variable meaning
Remarks
Field type
name
Name
Chinese name
String
gender
Gender
Male/Female
String
work_start_year
Start working years
Four-digit year, such as 2013
String
national_identity_number
ID number
Chinese resident identity card number
String
date_of_birth
Birthday
Date of birth, such as 1981-02-01, if there is only year and month, it will be 1981-02
String
ethnic
Ethnicity
56 ethnic groups in China, such as Han, Zhuang
String
current_location
Location
City or region, such as Xicheng, Beijing, Changsha, Hunan
String
current_location_norm
Location (standardized)
Location standardization China-Beijing-Beijing-Changping District, only supports China region
String
detailed_location
Detailed address
Specific family residence, such as No. 1, Laodong West Road, Yuhua District, Changsha City
String
age
Age
Current age, integer
Int
num_work_experience
Work experience
Current working years, integer
Int
current_company
Current company
String
current_position
Current position
String
school_name
Graduation school
Highest academic degree school
String
school_type
Graduation school category
985 211/211/null value
String
degree
Educational qualifications
Highest academic qualifications Ph.D./MBA/EMBA/Master's/Undergraduate/College/High School/Technical Secondary School/Junior High School
String
major
Major
Highest degree major
String
desired_position
Desired position
String
current_salary
Current salary
Current salary or current salary range, such as 20,000-30,000 yuan/month, 150,000-300,000 yuan, etc., whichever is based on the resume
String
desired_salary
Expected salary
Expected salary or expected salary range, such as 2001-2999 yuan/month, 10k-12k, etc., whichever is based on the resume
String
industry
Industry
Industry of latest job
String
desired_industry
Desired industry
The candidate mentioned the desired industry. This field currently only supports Chinese resume extraction
String
current_status
Job search status
Employed, looking for a job/Employed, considering good career opportunities/Employed, not considering other opportunities for the time being/Resigned/Fresh graduates
String
political_status
Political outlook
Party members/league members/people
String
marital_status
Marital status
Single/Married
String
zipcode
Zip code *
6-digit zip code, such as 510610
String
birthplace
Place of birth
Place of birth, such as Guangzhou, Guangdong, Luoyang, Jiangsu. Subject to resume description
String
birthplace_norm
Place of origin (standardized)
Standardized place of origin region, such as China-Jiangsu-Nanjing, only supports China region
String
expect_location
Expected working region
Expected working city or region, multiple regions separated by commas, such as Beijing, Shanghai
String
expect_location_norm
Expected working area (standardized)
Expected working city or region, multiple areas are separated by English commas, which are standardized place names, China-Guangdong-Guangzhou, China-Guangdong-Shenzhen, only supports Chinese regions
String
lastupdate_time
Resume parsing completion time
Resume parsing request completion time format is "2020-10-09-06-23-15"
String
recent_graduate_year
Recent graduation year
Indicates the year in which the candidate graduated from the most recent academic qualification, such as 2020
String
professional_level
Candidate's professional level
Evaluate the candidate's level based on experience, junior/intermediate/senior/senior. This field currently only supports Chinese resume extraction
The work experience variable name is work_experience and the variable type is array[object]
Variable name
Variable meaning
Remarks
Field type
start_time_year
Start time year
4-digit year, 2016
String
start_time_month
Start time month
2-digit month, 01
String
end_time_year
End time year
4-digit year, 2018
String
end_time_month
End time month
2-digit month, 05
String
still_active
Is it still in place
1/0, 1 means it is still in its position
Int
company_name
Company name
String
department
Department
String
location
Location
String
job_title
Position name
String
description
Job description
String
industry
Company industry
The company's industry. If it is not filled in and a candidate profile is used, the company's industry will be automatically inferred based on the portrait model
String
job_function
Job function
Job function
String
company_size
Company size
Number of people in the company, 100-499 people, more than 1000 people, etc.
String
company_type
Company type
Company type, such as private, state agency, individual, etc., please refer to the resume description
String
salary
Salary level
The salary level of this position, for example, 3000-5000 yuan/month
String
underling_num
Number of subordinates
Number of subordinates to manage, 10 people
String
report_to
Reporting object
The resume mentions the reporting object, such as general manager
String
skills
Work skills
The skills used in this work experience. This field currently only supports Chinese resume extraction
The project experience variable name is project_experience and the variable type is array[object]
Variable name
Variable meaning
Remarks
Field type
start_time_year
Start time year
4-digit year, 2014
String
start_time_month
Start time month
2-digit month, 01
String
end_time_year
End time year
4-digit year, 2014
String
end_time_month
End time month
2-digit month, 03
String
still_active
Whether it is still
1/0, 1 means the experience is still continuing
Int
project_name
Project name
String
company_name
The company to which the project belongs
This field currently only supports Chinese resume extraction
String
location
Location
Project location city or region
String
job_title
Position name
String
job_function
The standard function to which the position belongs
If a candidate profile is used, the standard function of the project will be automatically inferred based on the portrait model, otherwise it will be an empty string
String
description
Project description
String
skills
Project skills
The skills used in this project experience. This field currently only supports Chinese resume extraction
To return the original text, you need to set the request query rawtext=1, the original text variable name is resume_rawtext, and the variable type is string
packagemainimport("bytes""crypto/tls""fmt""log""net/http""os""encoding/base64""encoding/json""bufio""io/ioutil")// Creates a new file upload http requestfuncnewfileUploadRequest(uristring,pathstring)(*http.Request,error){file,err:=os.Open(path)iferr!=nil{returnnil,err}deferfile.Close()// Read entire JPG into byte slice.reader:=bufio.NewReader(file)content,_:=ioutil.ReadAll(reader)// Encode as base64.encoded:=base64.StdEncoding.EncodeToString(content)values:=map[string]string{"resume_base":encoded,"file_name":path}jsonValue,_:=json.Marshal(values)req,err:=http.NewRequest("POST",uri,bytes.NewBuffer(jsonValue))req.Header.Set("Content-Type","application/json")req.Header.Set("id","your_client_id")//替换为您的IDreq.Header.Set("secret","your_client_secret")//替换为您的密匙returnreq,err}funcapi_cv(file_pathstring){request,err:=newfileUploadRequest("http://api.xiaoxizn.com/v1/parser/parse_base?avatar=1&handle_image=1&rawtext=1&parse_mode=fast",file_path)iferr!=nil{log.Fatal(err)}tr:=&http.Transport{TLSClientConfig:&tls.Config{InsecureSkipVerify:true},}client:=&http.Client{Transport:tr}resp,err:=client.Do(request)iferr!=nil{log.Fatal(err)}else{body:=&bytes.Buffer{}_,err:=body.ReadFrom(resp.Body)iferr!=nil{log.Fatal(err)}resp.Body.Close()fmt.Println(body)}}funcmain(){api_cv("./resume.txt")//替换为您的简历}
Javascript
This code requires npm install request to be installed.
Whether to return to parsing the resume content, 1 returns, 0 does not return
rawtext
Int
No
Whether to return the original resume content when parsing the resume content, 1 returns, 0 does not return
handle_image
Int
No
Whether to process image resumes, 1 will process it, 0 will not process it
avatar
Int
No
Whether to extract resume avatar, 1 will be processed, 0 will not be processed
parse_mode
String
No
SIKAI's original parsing mode, customers can choose the most suitable resume parsing mode according to specific needs, fast extreme speed mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_mode
String
No
Image to text OCR mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_service
String
No
OCR service provider, tencent Tencent OCR, alicloud Alibaba OCR, baidu Baidu OCR, the default is Baidu OCR (local deployment only)
Request content description (body)
Parameter
Parameter type
Required
Description
resume_base
String
Yes
Base64 encoded resume file content
file_name
String
Yes
Resume file name (please make sure the suffix is correct)
Please refer to Error code summary, if the parsing is successful, it will be 0
Int
errormessage
Error message
Parsing error message
String
version
Version
Resume parsing version
String
cv_language
Resume language
zh, zh/en, en
String
src_site
Resume source
zhilian, 51job
String
avatar_data
Resume avatar picture
Resume avatar picture in BASE64 format. If there is no avatar, an empty string will be returned
String
avatar_url
The URL where the resume avatar picture is located
If the avatar picture in the resume is in the form of a link, save the link URL where the avatar is located. If there is no link, an empty string will be returned
String
parsing_result
Chinese parsing result
Returned when parsing_result=1, please refer to Return parsing result list, if there is no parsing result, it will be {}
Object
english_parsing_result
English parsing result
Returned when parsing_result=1, please refer to Return parsing result list, if there is no parsing result, it will be {}
Note: The fields returned by Chinese (parsing_result) and English (english_parsing_result) parsing are the same. Please refer to the returned parsing result list.
Send the json format that has been parsed by SIKAI resume and return the resume portrait analysis results. Need resume parsing with SIKAI
The fields in parsing_result in json format are exactly the same
Whether to return to parsing the resume content, 1 returns, 0 does not return
rawtext
Int
No
Whether to return the original resume content when parsing the resume content, 1 returns, 0 does not return
handle_image
Int
No
Whether to process image resumes, 1 will process it, 0 will not process it
avatar
Int
No
Whether to extract resume avatar, 1 will be processed, 0 will not be processed (local deployment only)
parse_mode
String
No
SIKAI's original parsing mode, customers can choose the most suitable resume parsing mode according to specific needs, fast extreme speed mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_mode
String
No
Image to text OCR mode, general normal mode, accurate high-precision mode, the default parsing mode is normal mode
ocr_service
String
No
OCR service provider, tencent Tencent OCR, alicloud Alibaba OCR, baidu Baidu OCR, the default is Baidu OCR (local deployment only)
Request content description (body)
Parameter
Parameter type
Required
Description
file
File
Yes
Original resume file
Example of request content structure:
{"file":{原始简历},}
Return result description
Variable name
Variable meaning
Remarks
Field type
cv_name
Resume file name
System cache file name
String
cv_id
Resume ID
System cached resume ID
String
errorcode
Error code
Please refer to Error code summary, if the parsing is successful, it will be 0
Int
errormessage
Error message
Parsing error message
String
version
Version
Resume parsing version
String
cv_language
Resume language
zh, zh/en, en
String
src_site
Resume source
zhilian, 51job
String
avatar_data
Resume avatar picture
Resume avatar picture in BASE64 format. If there is no avatar, an empty string will be returned
String
avatar_url
The URL where the resume avatar picture is located
If the avatar picture in the resume is in the form of a link, save the link URL where the avatar is located. If there is no link, an empty string will be returned
String
parsing_result
Chinese parsing result
Returned when parsing_result=1, please refer to Return parsing result list, if there is no parsing result, it will be {}
Object
english_parsing_result
English parsing result
Returned when parsing_result=1, please refer to Return parsing result list, if there is no parsing result, it will be {}
Note: The fields returned by Chinese (parsing_result) and English (english_parsing_result) parsing are the same. Please refer to the returned parsing result list.
Based on information such as resume work experience, project experience, and description skills, SIKAI knowledge graph and machine learning model are used to predict comprehensive resume skills. Predicted skills will cover summarizing the skills already on the resume, and further expand to skills that do not appear directly in the resume but are related. The skill score in the returned result corresponds to the correlation coefficient between the skill and the resume.
The candidate skills variable name is predicted_skills and the variable type is array[object]
Variable name
Variable meaning
Remarks
Field type
score
Professional skill score
Corresponding to the professional skill score formula, ranging from 0-1
Based on resume work experience, project experience, training experience and other information, SIKAI knowledge graph and machine learning model are used to predict multi-level job titles suitable for candidates. The job titles from the first level to the third level range from broad to detailed. The position score in the returned results corresponds to the correlation coefficient between the position and the resume.
The candidate title variable name is predicted_titles and the variable type is array[object]
Variable name
Variable meaning
Remarks
Field type
score
Position score
The position name corresponds to the fraction, ranging from 0-1
Based on information such as resume work experience, educational experience, candidate's salary and industry average, industry information, frequency of job changes, etc., the SIKAI machine learning model is used to predict the candidate's job-hopping rate. The higher the score, the more likely the candidate is to change jobs. If the resume clearly mentions that you are looking for a job, the job-hopping rate is 1
The candidate job-hopping rate variable name is predicted_turnover, and the variable type is double
Variable name
Variable meaning
Remarks
Field type
predicted_turnover
Job-hopping rate prediction
The candidate's current job-hopping probability, ranging from 0-1
Double
Sample example
"predicted_turnover":0.8724
Salary forecast
Based on resume work experience, education experience, project experience, training experience, highest level of study, major, working years, professional title and other information, use the SIKAI machine learning model to predict the candidate's salary.
The candidate salary prediction variable is named predicted_salary and the variable type is string
Variable name
Variable meaning
Remarks
Field type
predicted_salary
Salary prediction
Nine levels in total under_4000, 4000_to_6000, 6000_to_8000, 8000_to_10000, 10000_to_15000, 15000_to_20000, 20000_to_30000, 30000_to_40000, 40000+
String
Sample example
"predicted_salary":"10000_to_15000"
Desired salary withdrawal
Directly extract the expected salary filled in by the candidate from the resume.
The candidate's desired salary variable is named desired_salary and the variable type is string
Variable name
Variable meaning
Remarks
Field type
desired_salary
Subjective expected salary
Nine levels in total under_4000, 4000_to_6000, 6000_to_8000, 8000_to_10000, 10000_to_15000, 15000_to_20000, 20000_to_30000, 30000_to_40000, 40000+
String
Sample example
"desired_salary":"10000_to_15000"
Overall ability value evaluation
Based on the comprehensive description of the candidate's resume, predict the candidate's overall ability score. The educational background index is based on academic qualifications, school rankings, performance points and other factors; the honor index is based on resume award information; the language index is based on language type; the leadership index is based on work project experience and professional titles; the social activity index is based on resume social experience; the work experience index is based on the candidate's work experience, years, position, etc.
The variable name of the candidate's overall ability value is predicted_capability, and the variable type is object
Based on the resume's work experience, education experience, project experience and other descriptions, predict the candidate's affiliation score for the following 12 major industries. The higher the score, the higher the degree of affiliation to the industry.
The candidate industry affiliation variable is named predicted_industry and the variable type is object
Variable name
Variable meaning
Remarks
Field type
Internet
Internet industry affiliation
0-10 score
Double
Product
Product industry affiliation
0-10 score
Double
Personnel/Administration/Senior Management
Personnel/Administration/Senior Management Industry Belonging Degree
0-10 Score
Double
Consulting/Legal/Civil Service
Consulting/Legal/Civil Service Industry Belonging Degree
0-10 Score
Double
Engineer
Engineer industry affiliation
0-10 score
Double
Construction/Real Estate
Construction/Real Estate Industry Belonging Degree
0-10 Score
Double
Education/Translation/Service Industry
Education/Translation/Service Industry Industry Belonging Degree
0-10 Score
Double
Production/Purchasing/Logistics
Production/Purchasing/Logistics Industry Belonging Degree
0-10 Score
Double
Biological/pharmaceutical/medical/nursing
Biological/pharmaceutical/medical/nursing industry affiliation
0-10 score
Double
Operation/Customer Service/Sales/Market
Operation/Customer Service/Sales/Market Industry Belonging Degree
Based on the job change experience of the resume and the type of each extracted work experience, the candidate's loyalty to the company and industry functions stability is calculated through the big data algorithm. The variable type is object
Variable name
Variable meaning
Remarks
Field type
average_job_function_time
The average stay time of each function, if the function has not been changed, it is Null
In units of months
Double
average_industry_time
The average length of stay in each industry, if you have not changed industries, it is Null
In units of months
Double
average_work_time
The average length of stay in each job, or Null if you have not changed jobs
In monthly units
Double
work_stability
Comprehensive judgment of the candidate's job loyalty
Through tens of millions of data, we summarize the reasons for success in the workplace and provide you with the most scientific way to decode the potential advantages of candidates. The variable name of resume highlight analysis is highlights, and the variable type is object
Summarize and analyze potential risks in the workplace through tens of millions of data to help you discover potential risk factors of candidates. The resume risk analysis variable name is risks and the variable type is object
Combining machine learning and recruitment knowledge graph technology to provide candidates with a standardized tag management system, it is convenient for recruiters to fully understand the candidates by just reading the tags. At the same time, knowledge graph technology is used,
Can provide multiple dimensions of implicit information, such as candidate professional skills (each skill can obtain its category, front-end, back-end, algorithm, product management, etc.), historical company information (such as providing the industry status of the company based on the knowledge graph),
Graduation school information (whether it is a prestigious overseas school, country, whether it is a top domestic school, whether it is 985, 211, key undergraduate), candidate's standard industry background (according to the company, the projects done combined with the knowledge graph provide the candidate's industry background), language mastery (language proficiency is inferred from language test information, study abroad country, etc.), candidate's professional level,
Do you have management experience, soft skills labels (written expression ability, logical thinking, communication skills, etc.), etc.
The standardized job parsing variable name is tags, the variable type is Object, and the * field indicates that it is still under development.
Variable name
Variable meaning
Remarks
Field type
basic
Basic information tag
Type is experience, level, expect_location, current_location, salary, political_status, age, gender
Array[Object]
basic.tag
Basic information tag name
String
basic.type
Tag type
String
education
Education background tag
Type is degree, abroad, abroad_country, major, school_level, *publication
Array[Object]
education.tag
Education background tag name
String
education.type
Tag type
String
professional
Professional tag
Type is standard_title, job_title, industry, management, company_class
Array[Object]
professional.tag
Professional tag name
String
professional.type
Label type
String
skills
Skill tags
Types are professional_skill, soft_skill
Array[Object]
skills.tag
Skill tag name
String
skills.type
Tag type
String
skills.subclass
Skill type category
String
others
Other information tags
Type is language, certificate, award
Array[Object]
others.tag
Other information tag name
String
others.type
Tag type
String
others.level
Mastery level, currently only language mastery level is supported
packagemainimport("bytes""crypto/tls""fmt""log""net/http""os""encoding/base64""encoding/json""bufio""io/ioutil")// Creates a new file upload http requestfuncnewfileUploadRequest(uristring,pathstring)(*http.Request,error){file,err:=os.Open(path)iferr!=nil{returnnil,err}deferfile.Close()// Read entire JPG into byte slice.reader:=bufio.NewReader(file)content,_:=ioutil.ReadAll(reader)// Encode as base64.encoded:=base64.StdEncoding.EncodeToString(content)values:=map[string]string{"resume_base":encoded,"file_name":path}jsonValue,_:=json.Marshal(values)req,err:=http.NewRequest("POST",uri,bytes.NewBuffer(jsonValue))req.Header.Set("Content-Type","application/json")req.Header.Set("id","your_client_id")//替换为您的IDreq.Header.Set("secret","your_client_secret")//替换为您的密匙returnreq,err}funcapi_cv(file_pathstring){request,err:=newfileUploadRequest("http://api.xiaoxizn.com/v1/bundle/analyze_base",file_path)iferr!=nil{log.Fatal(err)}tr:=&http.Transport{TLSClientConfig:&tls.Config{InsecureSkipVerify:true},}client:=&http.Client{Transport:tr}resp,err:=client.Do(request)iferr!=nil{log.Fatal(err)}else{body:=&bytes.Buffer{}_,err:=body.ReadFrom(resp.Body)iferr!=nil{log.Fatal(err)}resp.Body.Close()fmt.Println(body)}}funcmain(){api_cv("./resume.txt")//替换为您的简历}
Javascript
This code requires npm install request to be installed.
The filter parameters do not meet the requirements
80
Resume parsing server internal error
81
English server internal error
90
This file format is not supported
91
Image file parsing is not supported
92
The document is not a real resume
93
English resume parsing is not supported
Talent Database
Interface description
Insert original resume
Send resume information and save resumes to candidate-job matching and talent search databases. Currently, resume insertion and deduplication supports the following four modes:
overwrite (only keep newly inserted resumes, delete all previous duplicate resumes), skip (only keep resumes already in the database, new ones are not inserted), keep_latest (only keep the resumes with the latest update year according to intelligent algorithms), keep_both (do not remove duplicates, insert resumes directly)
Whether to process image resumes, 1 will process it, 0 will not process it. Default is 0.
Request content description (body)
Parameter
Parameter type
Required
Description
resume_base
String
Yes
The base64-encoded resume file content.
file_name
String
Yes
Resume file name (please make sure the suffix is correct).
folder_name
String
No
Target folder name, can be used for quick search, default is default-folder.
index
String
No
The name of the resume library Index that needs to be inserted (only for local deployment), the default is resumes.
update_mode
String
No
The deduplication mode of inserting resume, now supports overwrite, skip, keep_both, keep_latest and the default is keep_both.
predicted_result
Int
No
Whether to perform portrait analysis and store it together when inserting, 1 means to perform portrait analysis, 0 means not to perform it. Default is 0. If the portrait is not purchased for local deployment, it cannot be set to 1.
This API is for local deployment only. Send SIKAI resume parsed json format, and store the resume in the candidate-job matching database. It needs to be exactly the same as the fields in the SIKAI resume parsing json format parsing_result. Currently, resume insertion and deduplication supports the following four modes:
overwrite (only keep newly inserted resumes, delete all previous duplicate resumes), skip (only keep resumes already in the database, new ones are not inserted), keep_latest (only keep the resumes with the latest update year according to intelligent algorithms), keep_both (do not remove duplicates, insert resumes directly)
Target folder name, can be used for quick search, default is default-folder.
index
String
No
The name of the resume library Index that needs to be inserted (only for local deployment), the default is resumes.
update_mode
String
No
The deduplication mode for inserting resume, now supports overwrite, skip, keep_both, keep_latest and the default is keep_both.
tags
Object
No
Additional custom tag fields can be inserted. You need to add a custom tag name and format through the corresponding API in advance, please refer to Add a custom tag field
candidates
Array[Object]
No
Deliver candidate information. It can contain candidate_id, job_id, job_title, stage_id, stage_type, consideration_status, creator_id, created_at, source
Resume file name (please make sure the suffix is correct).
folder_name
String
No
The name of the target folder for resume plagiarism checking, which can be used for quick search. The default is default-folder.
index
String
No
The Index name of the target resume database that needs to be checked (only for local deployment), the default is resumes.
source
Array[String]/String
No
Suspected duplicate resume fields that need to be returned. If you want to return all basic information, enter source="parsing_result.basic_info", and an empty array will be returned by default
max_return
Int
No
Maximum number of suspected duplicate resumes returned, default 100 (only local deployment required)
Please refer to Error code summary, if obtained successfully, it will be 0
Int
errormessage
Error message
Error message
String
duplicate_ids
Suspected duplicate resume ID
Suspected duplicate resume CV_ID
Array[String]
duplicate_resumes
Suspected duplicate resume content
Control the returned result containing fields through the source field. By default, duplicate resume content will not be returned and an empty array will be returned
The name of the target folder for resume plagiarism checking, which can be used for quick search. The default is default-folder.
index
String
No
The Index name of the target resume database that needs to be checked (only for local deployment), the default is resumes.
source
Array[String]/String
No
Suspected duplicate resume fields that need to be returned. If you want to return all basic information, enter source="parsing_result.basic_info", and an empty array will be returned by default
max_return
Int
No
Maximum number of suspected duplicate resumes returned, default 100 (only local deployment required)
Please refer to Error code summary, if obtained successfully, it will be 0
Int
errormessage
Error message
Error message
String
duplicate_ids
Suspected duplicate resume ID
Suspected duplicate resume CV_ID
Array[String]
duplicate_resumes
Suspected duplicate resume content
Control the returned result containing fields through the source field. By default, duplicate resume content will not be returned and an empty array will be returned
Target folder name, can be used for quick search, default is default-folder.
index
String
No
Resume database Index name (only for local deployment), the default is resumes.
offset
Int
No
Query the starting position. Default is 0, range is 0-10000
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
Return result description
Variable name
Variable meaning
Remarks
Field type
errorcode
Error code
Please refer to Error code summary, if the resume is successfully listed, it will be 0
Int
errormessage
Error message
Error message
String
hits
Number of resumes
Total number of resumes in the corresponding target resume database
Please refer to Error code summary, if the deletion is successful, it will be 0
Int
errormessage
Error message
Error message
String
Sample example
{"errorcode":0,"errormessage":"succeed"}
Add custom fields (local)
This API is for local deployment only. Add the specified type to the specified INDEX to provide fields for intelligent search. After the addition is completed, it is recommended to wait 2-3 seconds for the background search database to be updated before inserting the resume and searching. Before the new field is added, no resume containing this field cannot be inserted into the target INDEX, otherwise a field already exists error will occur. The newly added fields need to exist in the resume inserted later and are encapsulated using tags. If the newly added field is named customized_tag, the field information inserted into the resume must be placed in the following sample. For specific samples, please refer to insert analytical resume.
The name of the newly added searchable field. The document will be subsequently referred to as <tag>. Do not include characters such as ., min, max, etc. in the name. Field names only support English letters and underscores.
tag_type
String
Yes
The field type of newly added searchable fields, currently supports text/array_text/array_keyword/integer/float/date/bool
Example of request content structure:
{"tag_name":"<tag>","tag_type":"text"}
Custom field type description (tag-body)
tag_type The optional types are shown in the following table.
Field type
Description
Sample
text
Text type data
passed the interview, failed the interview
array_text
Text type data array
ARRAY[java, c++, python]
array_keyword
Text keyword type data array
ARRAY[java, c++, python]
integer
Integer data
1, 8
float
Floating point type data
1.03, 4.88
date
Date type data
Currently ES7.5 version and above support 2019/05/01, 2019-05-01, 2019-05-01 11:11:11, 2019-05-01 11:11:11.111, 2019-05-01T11:11:11.111, 2019/05/01 11:11:11.111, ES7.4 and below only support 2019-05-01T11:11:11 Format
bool
Boolean data
True, False
Custom field search method description (tag-search)
Assume that the inserted field name is customized_tag. Do not include characters such as ., min, max, etc. in the name. Field names only support English letters and underscores. For the search method, please refer to Search Resume.
Field type
Supported search fields
Reference sample
Search method description
Description
text
tags.min_<tag>
tags.min_customized_tag
Text minimum value search, just ordinary string size comparison
If searching for abc, abcd can be filtered
text
tags.max_<tag>
tags.max_customized_tag
Text maximum value search, just ordinary string size comparison
If searching for abc, abcd cannot pass the filter
text
tags.<tag>
tags.customized_tag
Text segmentation search
If you search for big data R&D, both the words big data and R&D will pass the filter
text
tags.<tag>.keyword
tags.customized_tag.keyword
Text keyword search
If you search for big data research and development, the field must be exactly equal to big data research and development to pass the filter
array_text
tags.<tag>
tags.customized_tag
Use text array for word segmentation search, AND logic
If searching for ARRAY[java, big data], all elements of the array need to be included to pass the filtering
array_text
tags.<tag>.or
tags.customized_tag.or
Use text array for word segmentation search, OR logic
If searching for ARRAY[java, big data], as long as it contains java, big data, any one of them can pass the filter
array_keyword
tags.<tag>
tags.customized_tag
Use text array for keyword search, AND logic
If searching for ARRAY [java, big data], all elements of the array need to be included (the text is exactly the same) to pass the filter
array_keyword
tags.<tag>.or
tags.customized_tag.or
Use text array for keyword search, OR logic
If you search for ARRAY[java, big data], as long as it contains (the same text) java, big data, any one of them can pass the filter
integer
tags.min_<tag>
tags.min_customized_tag
Integer type minimum value search
If you search for 5, only the value greater than or equal to 5 will pass the search
integer
tags.max_<tag>
tags.max_customized_tag
Integer type maximum value search
If you search for 5, only the value less than or equal to 5 will pass the search
integer
tags.<tag>
tags.customized_tag
Integer type equals search
If searching for 5, only the value equal to 5 will pass the search
float
tags.min_<tag>
tags.min_customized_tag
Floating point type minimum value search
If you search for 5.0, only the value greater than or equal to 5.0 will pass the search
float
tags.max_<tag>
tags.max_customized_tag
Floating point type maximum value search
If you search for 5.0, only the value less than or equal to 5.0 will pass the search
date
tags.min_<tag>
tags.min_customized_tag
Time type minimum value search
For example, if you search for 2015-01-01T12:10:30, the search will only be passed if it is later than this time
date
tags.max_<tag>
tags.max_customized_tag
Time type maximum value search
For example, if you search for 2015-01-01T12:10:30, the search will only be passed if it is earlier than this time
bool
tags.<tag>
tags.customized_tag
Boolean type search
If you search for False, only the value that is False will pass the search
Return result description
Variable name
Variable meaning
Remarks
Field type
errorcode
Error code
Please refer to Error code summary, if the addition is successful, it will be 0
Int
errormessage
Error message
Error message
String
Sample example
{"errorcode":0,"errormessage":"succeed"}
Usage process case
This API allows users to customize the search filter field (FILTER) for the specified INDEX. Please refer to the following cases for specific usage:
A user added two new fields, interview stage (phase) and HR score (hr_score), in addition to the standard fields of SIKAI resume parsing, and hopes to add them to the search conditions.
This API can be used to update the existing database fields of the specified INDEX. The interview stage is divided into delivery/preliminary screening/first interview/second interview/OFFER, and the HR score is 0-5.
Insert a resume containing this field. The newly added field needs to be included under the field tags and can only be inserted using the insert-json API. The following format must be followed when inserting a resume.
Conduct a search. If you need to screen candidates who are in the face-to-face stage and have an HR score of 3 or above, you can refer to the following example.
This API is for local deployment only. Adds a new compound search field in the specified INDEX. Therefore, the compound search field is prefixed with ud, which means user-defined. Assuming the query_name is my_query, you can search by ud_my_query.
Note: The user database is initialized without any data. If the user needs to conduct a smart resume search test,
You need to first insert the matching resume into your exclusive talent database according to Insert Resume.
Once the resume is inserted, it is permanently valid and supports unlimited searches. For specific resume database operations, please refer to the resume database module.
Search criteria. The final returned results will be sorted by intelligent scoring based on the search criteria.
filter
Array[Object]
No
Filter condition. This condition is used for hard filtering and has nothing to do with the sorting of the returned results.
index
String
No
Query the database name. The default is resumes
offset
Int
No
Query the starting position. Default is 0, range is 0-10000
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
Search and filter conditions description (search-body)
A summary of fields that can be placed in query and filter. Multiple selection means that multiple search values can be searched together in the form of array, such as "school_name": ["Peking University", "Tsinghua University"]. Experience category indicates whether the search field can be classified into the same experience. If the search field experience category is the same, you can filter multiple fields within the same experience in the form of brackets, such as {"school_name": "Peking University", "major": "Finance"}.
If an array is entered in main when searching, each condition in main needs to be met before the results will be returned. If you want to use the intelligent multi-dimensional search mode, you can put multiple keywords in main and separate them with spaces, such as main": "java python", and the returned results will be intelligently sorted by considering both.
Parameters
Parameter type
Multiple selection
Experience category
Description
main
String
Yes
Full-text comprehensive search, only applicable within query conditions.
resume_rawtext
String
Yes
Raw text search.
folder_name
String
Yes
Resume folder name.
name
String
Is
the name.
gender
String
Is
Gender. Male, Female
political_status
String
Yes
Political status. Party members, League members, the masses
phone_number
String
Is
a mobile phone.
email
String
Yes
Email.
QQ
String
Yes
QQ number.
wechat
String
Yes
WeChat.
current_location
String
Yes
The current city. Currently only cities are supported, not provinces.
expect_location
String
Yes
Expected city. Currently only cities are supported, not provinces.
degree
String
Yes
Educational experience
Educational experience. Junior high school, Technical secondary school, High school, College, Undergraduate, Master, MBA, EMBA, PhD.
school_level
String
Yes
Education experience
School level. 211, 985.
school_name
String
Yes
Education experience
School name.
school_name.keyword
String
Yes
Education experience
School name. (exact match)
major
String
Yes
Education experience
Major.
courses
String
Yes
Education experience
Courses studied.
abroad
Int
No
Education experience
Whether it is an overseas institution, 1 means yes, 0 means no
abroad_country
String
Yes
Education experience
Overseas institution country
current_position
String
Yes
The current position.
desired_position
String
Yes
Desired position.
min_work_exp
Int
No
Minimum working years. 0-99
max_work_exp
Int
No
Maximum working years. 0-99
min_age
Int
No
Minimum age limit
max_age
Int
No
Maximum age limit
early_graduate_year
Int
No
Earliest graduation time
latest_graduate_year
Int
No
Latest graduation time
company_name
String
Yes
Work experience
Company name.
company_name.keyword
String
Yes
Work experience
Company name. (exact match)
industry
String
Yes
Work experience
Industry.
job_function
String
Yes
Work experience
The function of the position.
job_title
String
Yes
Work experience
Position name.
job_title.keyword
String
Yes
Work experience
Position name. (exact match)
department
String
Yes
Work experience
Department name.
work_description
String
Yes
Work experience
Description of work experience.
social_description
String
Yes
Description of social experience.
project_description
String
Yes
Project experience description.
training_description
String
Yes
Training experience
Description of training experience.
training_organization_name
String
Yes
Training experience
Name of training organization.
skills
String
Is
a skill.
it_skills
String
Yes
Computer skills.
business_skills
String
Yes
Business skills.
language
String
is the
language.
certificate
String
Yes
Certificate.
awards
String
Is the
award.
self_evaluation
String
Yes
Self-evaluation.
tags.<tag>
Custom search fields, please refer to Add custom tag fields (for local deployment only)
max_candidate_created_at
Datetime
No
The latest delivery time, the delivery field needs to be set. The format is 2021-04-22T10:45:00Z (only for local deployment)
min_candidate_created_at
Datetime
No
The earliest delivery time, the delivery field needs to be set. The format is 2021-04-22T10:45:00Z (only for local deployment)
candidate_consideration_status
Boolean
No
Candidate submission elimination status (for local deployment only)
The filter parameters do not meet the requirements
73
Update Index error
80
Request error
81
English server internal error
90
This file format is not supported
91
Image file parsing is not supported
92
The document is not a real resume
93
English resume parsing is not supported
101
Authorization failed
Candidate-Job Matching
Interface description
Match multiple resumes for a single position
Send the job title and job description, and return the most matching resume in the user's resume database. Users must first use the Candidate Data Module
This function can be used only by insert resume interface.
Note: The user database is initialized without any data. If the user needs to match multiple resumes,
You need to first insert the matching resume into your exclusive talent database according to Insert Resume.
Once the resume is inserted, it is permanently valid and can be quickly matched to multiple positions. For specific resume database operations, please refer to the resume database module.
Query the starting position. Default is 0, range is 0-10000.
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
Match multiple positions with a single original resume
Send a resume and return the most matching job title and position information in the user's job database. Users must first use the Job Database Module
This function can be used only by Insert Job Interface.
Note: The user database is initialized without any data. If the user needs to match multiple job positions,
You need to first insert the matching positions into your exclusive job database according to Insert Position.
Once inserted, the position is permanently valid and multiple resumes can be matched quickly. For specific job database operations, please refer to the job database module.
Whether to process image resumes, 1 will process it, 0 will not process it. Default is 0.
ocr_service
String
No
OCR service provider, tencent Tencent OCR, alicloud Alibaba OCR, baidu Baidu OCR, the default is Baidu OCR (local deployment only)
Request content description (body)
Parameter
Parameter type
Required
Description
resume
Object
Yes
Resume content.
resume.resume_base
String
Yes
The content of the resume file encoded by base64.
resume.file_name
String
Yes
Resume file name (please make sure the suffix is correct).
filter
Array[Object]
No
Only supports folder_name, which is the name of the target folder. It can be used for quick search. The default is default-folder.
offset
Int
No
Query the starting position. Default is 0, range is 0-10000.
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
Resume matching multiple positions after single parsing
Send the parsed json format resume and return the most matching job title and position information in the user's job database. Users must first use the Job Database Data Module
This function can be used only by Insert Job Interface.
Note: The user database is initialized without any data. If the user needs to match multiple job positions,
You need to first insert the matching positions into your exclusive talent database according to Insert Position.
Once inserted, the position is permanently valid and multiple resumes can be matched quickly. For specific job database operations, please refer to the job database module.
Only supports folder_name, which is the name of the target folder. It can be used for quick search. The default is default-folder.
offset
Int
No
Query the starting position. Default is 0, range is 0-10000.
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
Query the starting position. Default is 0, range is 0-10000.
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
The variable name of the original job parsing result is origin, the variable type is Object, and the * field indicates that it is still under development.
Variable name
Variable meaning
Remarks
Field type
company_name
Company name
Recruitment company name
String
job_title
Position name
Recruitment position name
String
job_function
Job function
Standard function to which the position belongs
String
department
Recruiting department
Description of the department where the position is located
String
degree
Educational requirements
Description of job education requirements
String
major
Professional requirements
Description of professional requirements for the position
Target folder name, can be used for quick search, default is default-folder.
tag
String
No
Returns the positions for a specific tag.
offset
Int
No
Query the starting position. Default is 0, range is 0-10000
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_RESULT_MAX_RETURN parameter
Return result description
Variable name
Variable meaning
Remarks
Field type
errorcode
Error code
Please refer to Error code summary, if the position is successfully listed, it will be 0
Int
errormessage
Error message
Error message
String
hits
Number of positions
The total number of positions in the corresponding target position database
The filter parameters do not meet the requirements
80
Resume parsing server internal error
81
English server internal error
90
This file format is not supported
91
Image file parsing is not supported
92
The document is not a real resume
93
English resume parsing is not supported
Knowledge Graph
Interface description
The current knowledge graph contains the following entities:
Entity type
Description
company
company
job_title
Position name
standard_job_title
Standard function name
university
school
school
College/department within a university
major
professional
skill
Skills
industry
Industry
Company search
Used to search for corresponding company entities through company-related information. You can enter any company's full name, company abbreviation, product name, etc. Returns the corresponding entity ID, company name, industry, location, logo and other basic information, including the search score.
It is used to complete the company name through part of the company name prefix when the search input is incomplete, and can identify the company name, company abbreviation, product name, etc. Compared with search, the completion interface is used to predict the user's search target company in real time while the user is typing. Therefore, the matching conditions are more relaxed than the search and only basic information such as company name and entity ID is returned.
Based on the information entered by the user, the company entities are aligned through the full company name, company abbreviation, product name, etc. Entity alignment that can be applied to company names in resume parsing results. The interface returns relatively complete company information.
Used to search for corresponding school entities through school-related information. You can enter the full name of any school, the abbreviation of the school, etc. Returns the corresponding entity ID, school name, location, logo and other basic information, including the search score.
It is used to complete the school name with partial study name prefixes when the search input is incomplete, and can identify the full name of the school, the abbreviation of the school, etc. Compared with search, the completion interface is used to predict the target school that the user is searching for in real time while the user is typing. Therefore, the matching conditions are more relaxed than the search and only basic information such as school name and entity ID is returned.
According to the information entered by the user, align the school entities through the full name of the school, the abbreviation of the school, etc. Entity alignment that can be applied to school names in resume parsing results. The interface returns relatively complete school information.
The type of the target entity, currently supports skill, job_title, standard_job_title, major, school. If not entered, the algorithm will automatically infer the entity type
Note: Parameters can be placed in the request path, such as:
Sends the entity name and target entity type, and returns the most closely connected entity of the specified type. Here are some examples that may answer the question:
What skills are most important for an algorithm engineer?
What major do JAVA engineers generally graduate from?
What types of jobs are suitable for graduates in applied mathematics?
What are the common job titles under the back-end development function?
The type of the target entity. Currently, job_title, standard_job_title, skill, major, all are supported as target queries. all means there is no limit to the type of returned entity
entity.src_entity_type
String
No
Enter the name of the entity. Currently, job_title, standard_job_title, major, skill are supported
offset
Int
No
Query the starting position. Default is 0, range is 0-10000.
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_KG_RESULT_MAX_RETURN parameter
Send the entity name and entity type and return the most similar entity information of the same type. Here are some examples that may answer the question:
What related skills do you need to master while mastering JAVA?
What are the subdivided directions for algorithm engineers?
Are there any similar institutions to Fudan University?
Enter the type of entity. Currently, job_title, skill, major, school are supported. If not entered, the algorithm will automatically determine the type
offset
Int
No
Query the starting position. Default is 0, range is 0-10000.
limit
Int
No
The quantity returned by the query. The default is 20, and the range is 1-1000. Local deployment users can modify it through the configuration file ES_KG_RESULT_MAX_RETURN parameter
Search score (the higher the score, the better the match)
Double
Sample example
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