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LinkedIn_AIHawk is a cutting-edge, automated tool designed to revolutionize the job search and application process on LinkedIn. In today's fiercely competitive job market, where opportunities can vanish in the blink of an eye, this program offers job seekers a significant advantage. By leveraging the power of automation and artificial intelligence, LinkedIn_AIHawk enables users to apply to a vast number of relevant positions efficiently and in a personalized manner, maximizing their chances of landing their dream job.
In the digital age, the job search landscape has undergone a dramatic transformation. While online platforms like LinkedIn have opened up a world of opportunities, they have also intensified competition. Job seekers often find themselves spending countless hours scrolling through listings, tailoring applications, and repetitively filling out forms. This process can be not only time-consuming but also emotionally draining, leading to job search fatigue and missed opportunities.
LinkedIn_AIHawk steps in as a game-changing solution to these challenges. It's not just a tool; it's your tireless, 24/7 job search partner. By automating the most time-consuming aspects of the job search process, it allows you to focus on what truly matters - preparing for interviews and developing your professional skills.
Intelligent Job Search Automation
Rapid and Efficient Application Submission
AI-Powered Personalization
Volume Management with Quality
Intelligent Filtering and Blacklisting
Dynamic Resume Generation
Secure Data Handling
Please watch this video to set up your LinkedIn_AIHawk: How to set up LinkedIn_AIHawk - https://youtu.be/gdW9wogHEUM
Confirmed succesfull runs OSs & Python: Python 3.10, 3.11.9(64b), 3.12.5(64b) . Windows 10, Ubuntu 22
Download and Install Python:
Ensure you have the last Python version installed. If not, download and install it from Python's official website. For detailed instructions, refer to the tutorials:
Download and Install Google Chrome:
Clone the repository:
git clone https://github.com/feder-cr/LinkedIn_AIHawk_automatic_job_application
cd LinkedIn_AIHawk_automatic_job_application
Activate virtual environment:
python3 -m venv virtual
source virtual/bin/activate
Install the required packages:
pip install -r requirements.txt
This file contains sensitive information. Never share or commit this file to version control.
email: [Your LinkedIn email]
password: [Your LinkedIn password]
openai_api_key: [Your OpenAI API key]
This file defines your job search parameters and bot behavior. Each section contains options that you can customize:
remote: [true/false]
true
to include remote jobs, false
to exclude themexperienceLevel:
true
, others to false
jobTypes:
true
, others to false
date:
true
, others to false
positions:
positions:
- Software Developer
- Data Scientist
locations:
locations:
- Italy
- London
distance: [number]
distance: 50
companyBlacklist:
companyBlacklist:
- Company X
- Company Y
titleBlacklist:
titleBlacklist:
- Sales
- Marketing
This file contains your resume information in a structured format. Fill it out with your personal details, education, work experience, and skills. This information is used to auto-fill application forms and generate customized resumes.
Each section has specific fields to fill out:
personal_information:
personal_information:
name: "Jane"
surname: "Doe"
date_of_birth: "01/01/1990"
country: "USA"
city: "New York"
address: "123 Main St"
phone_prefix: "+1"
phone: "5551234567"
email: "jane.doe@example.com"
github: "https://github.com/janedoe"
linkedin: "https://www.linkedin.com/in/janedoe/"
education_details:
This section outlines your academic background, including degrees earned and relevant coursework.
degree: The type of degree obtained (e.g., Bachelor's Degree, Master's Degree).
university: The name of the university or institution where you studied.
final_evaluation_grade: Your Grade Point Average or equivalent measure of academic performance.
start_date: The start year of your studies.
graduation_year: The year you graduated.
field_of_study: The major or focus area of your studies.
exam: A list of courses or subjects taken along with their respective grades.
Example:
education_details:
education_level: "Bachelor's Degree" institution: "University of Example" field_of_study: "Software Engineering" final_evaluation_grade: "4/4" start_date: "2021" year_of_completion: "2023" exam: Algorithms: "A" Data Structures: "B+" Database Systems: "A" Operating Systems: "A-" Web Development: "B"
experience_details:
This section details your work experience, including job roles, companies, and key responsibilities.
position: Your job title or role.
company: The name of the company or organization where you worked.
employment_period: The timeframe during which you were employed in the role (e.g., MM/YYYY - MM/YYYY).
location: The city and country where the company is located.
industry: The industry or field in which the company operates.
key_responsibilities: A list of major responsibilities or duties you had in the role.
skills_acquired: Skills or expertise gained through this role.
Example:
experience_details:
position: "Software Developer" company: "Tech Innovations Inc." employment_period: "06/2021 - Present" location: "San Francisco, CA" industry: "Technology" key_responsibilities:
projects:
Include notable projects you have worked on, including personal or professional projects.
name: The name or title of the project.
description: A brief summary of what the project involves or its purpose.
link: URL to the project, if available (e.g., GitHub repository, website).
Example:
projects:
- name: "Weather App"
description: "A web application that provides real-time weather information using a third-party API."
link: "https://github.com/janedoe/weather-app"
- name: "Task Manager"
description: "A task management tool with features for tracking and prioritizing tasks."
link: "https://github.com/janedoe/task-manager"
achievements:
Highlight notable accomplishments or awards you have received.
name: The title or name of the achievement.
description: A brief explanation of the achievement and its significance.
Example:
achievements:
name: "Employee of the Month" description: "Recognized for exceptional performance and contributions to the team."
name: "Hackathon Winner" description: "Won first place in a national hackathon competition."
certifications:
Include any professional certifications you have earned.
Example:
certifications:
"Certified Scrum Master"
"AWS Certified Solutions Architect"
languages:
Detail the languages you speak and your proficiency level in each.
language: The name of the language.
proficiency: Your level of proficiency (e.g., Native, Fluent, Intermediate).
Example:
languages:
language: "English" proficiency: "Fluent"
language: "Spanish" proficiency: "Intermediate"
interests:
Mention your professional or personal interests that may be relevant to your career.
interest: A list of interests or hobbies.
Example:
interests:
"Machine Learning"
"Cybersecurity"
"Open Source Projects"
"Digital Marketing"
"Entrepreneurship"
availability:
State your current availability or notice period.
notice_period: The amount of time required before you can start a new role (e.g., "2 weeks", "1 month").
Example:
availability:
notice_period: "2 weeks"
salary_expectations:
Provide your expected salary range.
salary_range_usd: The salary range you are expecting, expressed in USD.
Example:
salary_expectations:
salary_range_usd: "80000 - 100000"
self_identification:
Provide information related to personal identity, including gender and pronouns.
gender: Your gender identity.
pronouns: The pronouns you use (e.g., He/Him, She/Her, They/Them).
veteran: Your status as a veteran (e.g., Yes, No).
disability: Whether you have a disability (e.g., Yes, No).
ethnicity: Your ethnicity.
Example:
self_identification:
gender: "Female"
pronouns: "She/Her"
veteran: "No"
disability: "No"
ethnicity: "Asian"
legal_authorization:
Indicate your legal ability to work in various locations.
eu_work_authorization: Whether you are authorized to work in the European Union (Yes/No).
us_work_authorization: Whether you are authorized to work in the United States (Yes/No).
requires_us_visa: Whether you require a visa to work in the US (Yes/No).
requires_us_sponsorship: Whether you require sponsorship to work in the US (Yes/No).
requires_eu_visa: Whether you require a visa to work in the EU (Yes/No).
legally_allowed_to_work_in_eu: Whether you are legally allowed to work in the EU (Yes/No).
legally_allowed_to_work_in_us: Whether you are legally allowed to work in the US (Yes/No).
requires_eu_sponsorship: Whether you require sponsorship to work in the EU (Yes/No).
Example:
legal_authorization:
eu_work_authorization: "Yes"
us_work_authorization: "No"
requires_us_visa: "Yes"
requires_us_sponsorship: "Yes"
requires_eu_visa: "No"
legally_allowed_to_work_in_eu: "Yes"
legally_allowed_to_work_in_us: "No"
requires_eu_sponsorship: "No"
work_preferences:
Specify your preferences for work arrangements and conditions.
remote_work: Whether you are open to remote work (Yes/No).
in_person_work: Whether you are open to in-person work (Yes/No).
open_to_relocation: Whether you are willing to relocate for a job (Yes/No).
willing_to_complete_assessments: Whether you are willing to complete job assessments (Yes/No).
willing_to_undergo_drug_tests: Whether you are willing to undergo drug testing (Yes/No).
willing_to_undergo_background_checks: Whether you are willing to undergo background checks (Yes/No).
Example:
work_preferences:
remote_work: "Yes"
in_person_work: "No"
open_to_relocation: "Yes"
willing_to_complete_assessments: "Yes"
willing_to_undergo_drug_tests: "No"
willing_to_undergo_background_checks: "Yes"
The data_folder_example
folder contains a working example of how the files necessary for the bot's operation should be structured and filled out. This folder serves as a practical reference to help you correctly set up your work environment for the LinkedIn job search bot.
Inside this folder, you'll find example versions of the key files:
secrets.yaml
config.yaml
plain_text_resume.yaml
These files are already populated with fictitious but realistic data. They show you the correct format and type of information to enter in each file.
Using this folder as a guide can be particularly helpful for:
LinkedIn language To ensure the bot works, your LinkedIn language must be set to English.
Data Folder: Ensure that your data_folder contains the following files:
secrets.yaml
config.yaml
plain_text_resume.yaml
Run the Bot:
LinkedIn_AIHawk offers flexibility in how it handles your pdf resume:
--resume
option, the bot will automatically generate a unique resume for each application. This feature uses the information from your plain_text_resume.yaml
file and tailors it to each specific job application, potentially increasing your chances of success by customizing your resume for each position.
python main.py
data_folder
directory and run the bot with the --resume
option:
python main.py --resume /path/to/your/resume.pdf
TODO ):
If you encounter any issues, you can open an issue on GitHub.
Please add valuable details to the subject and to the description. If you need new feature then please reflect this.
I'll be more than happy to assist you!
LinkedIn_AIHawk provides a significant advantage in the modern job market by automating and enhancing the job application process. With features like dynamic resume generation and AI-powered personalization, it offers unparalleled flexibility and efficiency. Whether you're a job seeker aiming to maximize your chances of landing a job, a recruiter looking to streamline application submissions, or a career advisor seeking to offer better services, LinkedIn_AIHawk is an invaluable resource. By leveraging cutting-edge automation and artificial intelligence, this tool not only saves time but also significantly increases the effectiveness and quality of job applications in today's competitive landscape.
LinkedIn_AIHawk is still in beta, and your feedback, suggestions, and contributions are highly valued. Feel free to open issues, suggest enhancements, or submit pull requests to help improve the project. Let's work together to make LinkedIn_AIHawk an even more powerful tool for job seekers worldwide.
This project is licensed under the MIT License - see the LICENSE file for details.
LinkedIn_AIHawk is developed for educational purposes only. The creator does not assume any responsibility for its use. Users should ensure they comply with LinkedIn's terms of service, any applicable laws and regulations, and ethical considerations when using this tool. The use of automated tools for job applications may have implications on user accounts, and caution is advised.