https://github.com/pacemakerx/linkedintel
An AI-powered LinkedIn automation tool built with Python and Selenium. It scrapes your feed, analyzes post content using Gemini/OpenAI, and performs intelligent interactions like liking and commenting—based on engagement potential. Includes cookie-based login, human-like delays, and modular architecture for extension.
https://github.com/pacemakerx/linkedintel
automation gemini-api python selenium selenium-webdriver
Last synced: 8 months ago
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An AI-powered LinkedIn automation tool built with Python and Selenium. It scrapes your feed, analyzes post content using Gemini/OpenAI, and performs intelligent interactions like liking and commenting—based on engagement potential. Includes cookie-based login, human-like delays, and modular architecture for extension.
- Host: GitHub
- URL: https://github.com/pacemakerx/linkedintel
- Owner: PacemakerX
- Created: 2025-04-13T10:57:36.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-04-13T11:40:39.000Z (about 1 year ago)
- Last Synced: 2025-04-13T12:29:57.375Z (about 1 year ago)
- Topics: automation, gemini-api, python, selenium, selenium-webdriver
- Language: Python
- Homepage:
- Size: 45.9 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# LinkedIn Automation
A powerful Python-based automation tool that enhances your LinkedIn experience by streamlining networking and engagement to boost your professional presence.
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## 🚀 Features
- 👍 **Engagement Boost**: Automatically engage with posts from your network through likes and comments.
- 🤖 **AI-Powered Interactions**: Leverage Google Gemini to create natural, personalized messages.
- 🔄 **Session Management**: Utilize cookies for seamless authentication and session persistence.
- ⏱️ **Scheduling**: Set up automation tasks to run at specified times.
- 🛡️ **Safe Usage**: Built-in safeguards to maintain natural activity patterns and avoid LinkedIn restrictions.
- 🧠 **Smart Targeting**: Intelligently identify and engage with relevant connections based on your criteria.
## 🛠️ Tech Stack
### Core Technologies
- **Python**: Primary programming language for the automation scripts.
- **Selenium**: Browser automation framework for LinkedIn interactions.
- **Webdriver Manager**: Automated management of browser driver binaries.
- **Google Gemini AI**: Advanced AI model for generating natural text and interactions.
- **python-dotenv**: Environment variable management for secure configuration.
## 📋 Installation
```bash
# Clone the repository
git clone https://github.com/PacemakerX/LinkedIntel.git
cd LinkedIntel
# Set up virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Configure environment variables
cp .env.example .env
# Edit .env with your API keys and settings
# Set up cookies for authentication
cp cookies.example.json cookies.json
# Replace with your actual LinkedIn cookies
```
## 🔧 Configuration
### Requirements.txt
```
google-generativeai==1.10.0
openai==1.73.0
python-dotenv==1.1.0
selenium==4.31.0
webdriver-manager==4.0.2
```
### Cookie Authentication
This project uses cookie-based authentication to maintain LinkedIn sessions:
1. Log in to LinkedIn in your browser
2. Export your cookies to a `cookies.json` file (you can use browser extensions for this)
3. Place the file in the project root directory
4. An example structure is provided in `cookies.example.json`
### Environment Variables
Create a `.env` file with the following variables:
```
GEMINI_API_KEY=your_gemini_api_key
```
## 📝 Usage
```bash
# Run the main file
python main.py
```
## Link to the Repository:
## Feel free to connect with me!
