linkedin-ai 0.6.4

Automate searching for jobs and submitting applications on LinkedIn using OpenAI

linkedin-ai

Automate searching for jobs and submitting applications on LinkedIn using OpenAI.

• Why use LinkedIn AI?
• Features
• Installation
  • PyPi Install Command
  • From Source Install Commands
  • Chromedriver Download (REQUIRED)
  • OpenAI API Key Setup (REQUIRED)
• Usage: (How to run the LinkedIn Automator GUI App)
• Searching for Jobs
  • Search Filters and Job Collections
  • Removing Jobs From Search Results
  • Finding Easy-Apply Jobs
• Submitting Job Applications
  • Providing your Resume as Context for your AI
  • Training your AI to Answer Questions Like You
  • Full Automation
• Generating Custom Cover Letters
  • Cover Letter Options
  • Providing Cover Letter Examples
• Viewing and Managing your Saved Jobs DB
  • Filtering Saved Jobs
  • Opening Saved Jobs
  • Updating Saved Jobs
• Contributing
• License

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Why use LinkedIn AI?

Automate Finding Jobs.

Automate Filling Out and Submitting Job Applications

Easily View and Manage the Jobs You've Saved

Features

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Installation

Linkedin AI can be installed from PyPi or from source.

PyPi Install Command

pip3 install linkedin-ai

From Source Install Commands

git clone https://github.com/LucasFaudman/linkedin-ai.git
cd linkedin-ai
python3 -m venv .venv
source .venv/bin/activate
pip3 install -e .

IMPORTANT: After installing linkedin-ai, you will still need to download the correct Chromedriver AND setup your OpenAI API Key.

Chromedriver Download

Download the appropriate ChromeDriver for your Chrome version using getchromedriver.py (command below) or manually from the ChromeDriver website.

To find your Chrome version, go to chrome://settings/help in your browser.

getchromedriver

OpenAI API Key Setup

Instructions to setup your OpenAI API key can be found at this link

Once you have the path to your chromedriver and OpenAI API Key you are ready to use LinkedIn AI.

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Usage: (How to run the LinkedIn Automator GUI App)

Run the command below to open the LinkedIn Automator App:

linkedin-ai

This will use the default config path ./linkedin-ai-config.json

To specify a custom config path use the --config/-c argument:

linkedin-ai --config /path/to/custom/config.json

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Searching For Jobs

LinkedIn AI supports all LinkedIn Search Filters.

Search Filters and Job Collections

Removing Jobs From Search Results

Finding Easy-Apply Jobs

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Submitting Job Applications

Providing your Resume as Context for your AI

Training your AI to Answer Questions Like You

Full Automation

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Generating Custom Cover Letters

Cover Letter Options

Providing Cover Letter Examples

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Viewing and Managing your Saved Jobs DB

Filtering Saved Jobs

Opening Saved Jobs

Updating Saved Jobs

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Contributing

Contributions welcome! Whether you're interested in fixing bugs, adding new features, improving documentation, or sharing ideas, any input is valuable.

How to Contribute

1. Fork the Repository: Start by forking the repository on GitHub. This will create a copy of the project in your own GitHub account.

2. Clone the Repository: Clone the forked repository to your local machine.

   git clone https://github.com/LucasFaudman/linkedin-ai.git
   cd linkedin-ai
   

3. Create a Branch: Create a new branch for your changes.

   git checkout -b my-feature-branch
   

4. Make Changes: Make your changes in the code, documentation, or both.

5. Commit Changes: Commit your changes with a descriptive commit message.

   git add .
   git commit -m "Description of the changes"
   

6. Push Changes: Push your changes to your forked repository.

   git push origin my-feature-branch
   

7. Create a Pull Request: Go to the original repository and create a pull request from your branch. Provide a detailed description of your changes and any relevant information.

Issues

If you encounter any bugs, have suggestions, or need help, please open an issue on GitHub. Make sure to provide as much detail as possible, including steps to reproduce the issue, error messages, and screenshots if applicable.

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License

See LICENSE for details.