🚀 LinkedIn Automate Comment

Welcome to LinkedIn Automate Comment! This project leverages web scraping, sentiment analysis, and AI-driven text generation to automate meaningful LinkedIn interactions. 🎯

Table of Contents

• Project Overview
• Featured In
• How It Works
• Features
• Directory Structure
• Setup and Installation
• Usage
• Contributing
• License

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Project Overview

💡 LinkedIn Automate Comment simplifies professional networking by:

• ✅ Scraping LinkedIn posts from your feed.
• ✅ Performing sentiment analysis on posts and comments.
• ✅ Generating AI-powered, context-aware comments.
• ✅ Automating the posting of comments on LinkedIn.

Ideal for professionals who want to stay active on LinkedIn with minimal effort! 🚀

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Featured In

JWOC Winter of Code

JWoC provides a fully immersive learning experience for students and first-time contributors by promoting the wonders of open-source software and crafting a community of new and experienced technical developers. The best projects are selected for this program. Students get acquainted with the projects from the mentors during the Community Bonding Period. Students work on these projects during the coding phase. At the end of the coding period, the winners of the programs are announced on the basis of their contribution in terms of quantity as well as quality.

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How It Works 🛠️

1️⃣ Scrape Posts: web_scrapper.py logs into LinkedIn and collects posts. 2️⃣ Analyze Sentiment: analyze.py determines the tone of posts/comments. 3️⃣ Generate Comments: llm.py creates AI-powered, relevant responses. 4️⃣ Post Comments: test.py automates comment posting via Selenium.

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Features ✨

🎯 Web Scraping: Extracts LinkedIn posts efficiently. 📊 Sentiment Analysis: Evaluates post/comment tone. 🤖 AI-Powered Comments: Generates concise, relevant responses. ⚡ Automation: Uses a headless browser to post comments. 📄 PDF Reports: Exports insights as downloadable PDFs.

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Directory Structure 📁

Directory structure:
└── hiteshydv001-linkedin-automate-comment/
    ├── README.md
    ├── anlyze.py
    ├── contribution.md
    ├── linkedin_posts.csv
    ├── llm.py
    ├── main.py
    ├── requirements.txt
    ├── service.json
    ├── web_scrapper.py
    ├── .env.local
    ├── JWoC/
    │   └── Readme.md
    ├── agents/
    │   ├── __init__.py
    │   ├── agent_base.py
    │   ├── generate_comment_agent.py
    │   ├── refiner_agent.py
    │   ├── sanitize_data_tool.py
    │   ├── sanitize_data_validator_agent.py
    │   ├── sentiment_analysis_agent.py
    │   ├── summarize_tool.py
    │   ├── summarize_validator_agent.py
    │   ├── validator_agent.py
    │   ├── write_post_tool.py
    │   └── write_post_validator_agent.py
    ├── frontend/
    │   ├── README.md
    │   ├── components.json
    │   ├── eslint.config.mjs
    │   ├── next.config.ts
    │   ├── package-lock.json
    │   ├── package.json
    │   ├── postcss.config.mjs
    │   ├── tailwind.config.ts
    │   ├── tsconfig.json
    │   ├── .gitignore
    │   ├── public/
    │   │   └── linkedin-automation-icon.avif
    │   └── src/
    │       ├── app/
    │       │   ├── globals.css
    │       │   ├── layout.tsx
    │       │   ├── page.tsx
    │       │   ├── generate_comments/
    │       │   │   └── page.tsx
    │       │   ├── sentiment_analysis/
    │       │   │   └── page.tsx
    │       │   ├── summarize/
    │       │   │   └── page.tsx
    │       │   └── write_post/
    │       │       └── page.tsx
    │       ├── components/
    │       │   ├── main-nav.tsx
    │       │   ├── theme-provider.tsx
    │       │   └── ui/
    │       │       ├── button.tsx
    │       │       ├── card.tsx
    │       │       ├── dialog.tsx
    │       │       ├── dropdown-menu.tsx
    │       │       ├── form.tsx
    │       │       ├── input.tsx
    │       │       ├── label.tsx
    │       │       ├── select.tsx
    │       │       ├── tabs.tsx
    │       │       ├── textarea.tsx
    │       │       ├── toast.tsx
    │       │       └── toaster.tsx
    │       ├── hooks/
    │       │   └── use-toast.ts
    │       └── lib/
    │           └── utils.ts
    └── .github/
        ├── dependabot.yml
        └── workflows/
            └── codeql.yml

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Setup and Installation 📦

Prerequisites

• 🐍 Python 3.8+
• 🔑 Google API Key (for Generative AI)
• 🌍 Chrome & ChromeDriver (ensure compatibility)

Installation Steps

1️⃣ Clone the repository:

git clone https://github.com/hiteshydv001/linkedin-automate-comment.git
cd linkedin-automate-comment

2️⃣ Install required packages:

pip install -r requirements.txt

3️⃣ Configure environment variables in a .env file:

EMAIL=your_email@example.com
PASSWORD=your_password
GOOGLE_API_KEY=your_google_api_key

4️⃣ Ensure Chrome & ChromeDriver are installed.

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Usage 🏁

Step 1: Scrape LinkedIn Posts

python web_scrapper.py

Step 2: Perform Sentiment Analysis

python analyze.py

Step 3: Generate Comments

python llm.py

Step 4: Post Comments

python test.py

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Contributing 🌟

🎯 Contributions are welcome! Follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-name

3. Commit your changes:

   git commit -m "Add feature description"

4. Push to your branch:

   git push origin feature-name

5. Open a pull request. 🚀

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License ⚖️

This project is licensed under the MIT License. See the LICENSE file for details.

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🎉 Enjoy automating your LinkedIn interactions with LinkedIn Automate Comment! 🚀

📜 Contributing Guide for specific purposes and competitons ⚖️

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Please refer to our

• contribution.md for general open source contribution
• JWoC guide for contribution under JGEC Winter of Code