Social Media Content Agent System

A sophisticated multi-agent system that combines specialized AI agents to create engaging social media content. The system leverages a Research Agent for gathering accurate, up-to-date information and a Social Media Agent for crafting compelling posts with AI-generated visuals.

Features

• Automated research on any given topic using GPT-4.1-mini and web search
• AI-powered content generation for social media posts
• Automatic image generation matching the post content
• Markdown output with integrated images
• Hashtag generation for better social media engagement

Multi-Agent Architecture

The system employs a hierarchical multi-agent approach:

1. Research Agent (Information Gathering)

   • Conducts web searches to gather current information
   • Analyzes and synthesizes data from multiple sources
   • Provides structured research output to the Social Media Agent

2. Social Media Agent (Content Creation)

   • Processes research data into engaging social media content
   • Generates relevant hashtags for better reach
   • Creates matching images using AI
   • Ensures content aligns with platform best practices

Prerequisites

• Python 3.9+
• OpenAI API key

Installation

1. Clone the repository:

git clone https://github.com/yourusername/social-media-agent.git
cd social-media-agent

2. Install the required dependencies:

pip install -r requirements.txt

3. Set up your OpenAI API key as an environment variable:

export OPENAI_API_KEY='your-api-key-here'

Usage

Run the main script with a topic:

python main.py

The script will:

1. Research the given topic using the Research Agent
2. Generate a social media post with relevant hashtags
3. Create a matching image using AI
4. Save the output in a markdown file with the embedded image

Project Structure

• main.py - Main script containing the agent setup and execution logic
• result.md - Output file containing the generated content
• Generated images are saved in the root directory

Configuration

The project uses two specialized agents:

1. Research Agent

   • Uses GPT-4.1-mini model
   • Equipped with web search capabilities
   • Focuses on gathering and validating information
   • Provides structured data for content creation

2. Social Media Agent

   • Uses GPT-4.1-mini model
   • Orchestrates the content creation process
   • Can invoke the Research Agent for information gathering
   • Generates images using GPT-image-1 model
   • Handles final content formatting and optimization

Output Format

The generated content is saved in markdown format with:

• Main post content optimized for social media engagement
• Strategically selected hashtags for maximum reach
• AI-generated image that complements the post content

Benefits of Multi-Agent Approach

• Specialized Expertise: Each agent focuses on its core competency
• Enhanced Research Quality: Dedicated agent for information gathering
• Better Content Creation: Specialized agent for social media optimization
• Scalable Architecture: Easy to add new agents for additional functionality
• Modular Design: Agents can be updated or replaced independently

Example Output

See result.md for an example of generated content, which includes:

• Researched and fact-checked information
• Engaging social media post format
• Relevant hashtags
• AI-generated complementary image

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

MIT License