LinkedIn Content Agent 🚀

A CrewAI-powered system that researches trending topics using Linkup and creates engaging LinkedIn posts automatically.

Overview

This project uses CrewAI to orchestrate two specialized AI agents:

1. Research Agent - Uses Linkup API to find trending topics and industry insights
2. Content Creator Agent - Transforms research findings into engaging LinkedIn posts

Features

• 🔍 Real-time Research: Uses Linkup API to find current trends and professional insights
• 📝 AI-Powered Content Creation: Generates engaging LinkedIn posts optimized for the platform
• 🤖 Multi-Agent Workflow: Specialized agents work together seamlessly
• 🎯 Targeted Content: Option to research specific topics or discover general trends
• 📊 Professional Quality: Content optimized for LinkedIn's algorithm and audience

Setup

Prerequisites

• Python 3.9 or higher
• Linkup API key (Get one here)
• OpenAI API key (Get one here)

Installation

1. Clone and navigate to the project:

cd linkedin-content-agent

2. Create and activate virtual environment:

uv venv
source .venv/bin/activate

3. Install dependencies:

uv sync  

4. Set up environment variables:

# Copy the example file and edit it with your real API keys
cp .env.example .env

5. Test your setup:

uv run test_linkup.py

Usage

Basic Usage

Run the interactive workflow:

uv run crew.py

You'll be prompted to enter a specific topic or press Enter to research general trends.

Programmatic Usage

from crew import LinkedInContentCrew

# Initialize the crew
crew = LinkedInContentCrew()

# Create a LinkedIn post about a specific topic
result = crew.create_linkedin_post("artificial intelligence in healthcare")

# Or research without creating content
research = crew.research_only("remote work trends 2024")

Example Output

The system will generate a complete LinkedIn post like this:

🎯 The future of work isn't just remote—it's hyper-personalized.

I've been analyzing the latest workplace trends, and here's what's fascinating: 
Companies that customize work experiences to individual employee needs see 40% 
higher retention rates.

💡 Key insights:
→ Flexible schedules aren't enough anymore
→ Personalized learning paths drive engagement
→ Micro-feedback systems beat annual reviews
→ Purpose-driven projects increase productivity by 23%

The question isn't whether your workplace adapts—it's how quickly you can 
make it personal.

What's one way your organization personalizes the work experience?

#FutureOfWork #EmployeeEngagement #WorkplaceTrends #Leadership #PersonalizedWork

Project Structure

linkedin-content-agent/
├── agents/
│   ├── research_agent.py         # Linkup research agent
│   └── content_creator_agent.py  # LinkedIn content creator
├── tasks/
│   ├── research_task.py          # Research task definition
│   └── content_creation_task.py  # Content creation task
├── tools/
│   └── linkup_tool.py            # Linkup API integration
├── crew.py                       # Main orchestration file
├── .env.example                  # Environment variables template
└── README.md                     # This file

Workflow

1. Research Phase: The Research Agent uses Linkup to find trending topics and insights
2. Analysis Phase: The agent analyzes findings and creates a content brief
3. Creation Phase: The Content Creator Agent transforms research into an engaging LinkedIn post
4. Optimization: The post is formatted and optimized for LinkedIn's platform

Customization

Modify Agent Behavior

Edit the agent files in the agents/ directory to customize:

• Agent personalities and expertise
• Research focus areas
• Content style and tone

Adjust Task Parameters

Modify task files in the tasks/ directory to:

• Change research criteria
• Adjust content requirements
• Modify output formats

Extend Functionality

• Add more tools in the tools/ directory
• Create additional agents for specialized tasks
• Implement different content formats (Twitter, blog posts, etc.)

Debug Mode

Set verbose=True in the crew configuration for detailed logging:

crew = Crew(
    agents=[self.research_agent, self.content_creator_agent],
    tasks=[research_task, content_task],
    process=Process.sequential,
    verbose=True  # Enable debug mode
)

License

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

Support

For questions or issues:

1. Check the troubleshooting section above
2. Review the CrewAI documentation
3. Check Linkup API documentation
4. Open an issue in this repository