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AgenticFlow

AgenticFlow is an advanced AI-powered automation platform designed to streamline digital communication and content management. The system intelligently processes emails, generates context-aware responses, and transforms newsletters into engaging social media content across multiple platforms.

✨ Key Features

πŸ€– Intelligent Email Management

  • Automated Email Processing: Fetch and analyze incoming emails in real-time
  • AI-Powered Responses: Generate contextually relevant email replies
  • Newsletter Intelligence: Extract and categorize content from newsletters
  • Smart Prioritization: Automatically categorize and prioritize incoming messages

πŸ“± Social Media Automation

  • Multi-Platform Publishing: Seamless content distribution to Twitter, LinkedIn, and more
  • Platform-Optimized Content: Automatic formatting for each social network's requirements
  • Scheduled Posting: Plan and schedule content for optimal engagement
  • Content Enrichment: Auto-generate hashtags, mentions, and media attachments

🧩 AI Agent Ecosystem

  • CrewAI Orchestration: Coordinated team of specialized AI agents
  • Modular Architecture: Easily extensible with new capabilities
  • Self-Improving: Learns from user feedback and interactions

πŸš€ Modern Tech Stack

  • Frontend: React.js with Tailwind CSS for a responsive UI
  • Backend: FastAPI for high-performance async operations
  • Database: PostgreSQL with SQLAlchemy ORM
  • Authentication: JWT-based secure access
  • Task Queue: Asynchronous task processing
  • Comprehensive Logging: Built-in monitoring and debugging

πŸš€ Getting Started

Prerequisites

  • Python 3.10+
  • PostgreSQL 13+
  • Redis (for task queue)
  • Gmail API credentials
  • Social media API credentials (Twitter, LinkedIn)

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/AgenticFlow.git
    cd AgenticFlow
  2. Set up the backend:

    cd backend
    python -m venv venv
    source venv/bin/activate # On Windows: .\venv\Scripts\activate
    pip install -r requirements.txt
  3. Configure environment variables: Copy .env.example to .env and update with your credentials.

  4. Initialize the database:

    alembic upgrade head
  5. Start the development server:

    uvicorn main:app --reload

πŸ—οΈ Project Structure

AgenticFlow/
β”œβ”€β”€ backend/ # Backend application
β”‚ β”œβ”€β”€ agents/ # AI agent implementations
β”‚ β”œβ”€β”€ api/ # API endpoints
β”‚ β”œβ”€β”€ database/ # Database models and migrations
β”‚ β”œβ”€β”€ models/ # Pydantic models
β”‚ β”œβ”€β”€ services/ # Business logic
β”‚ β”œβ”€β”€ utils/ # Utility functions
β”‚ β”œβ”€β”€ main.py # FastAPI application
β”‚ └── requirements.txt # Python dependencies
β”œβ”€β”€ frontend/ # React frontend (coming soon)
β”œβ”€β”€ tests/ # Test suite
β”œβ”€β”€ .env.example # Example environment variables
β”œβ”€β”€ .gitignore
└── README.md # This file

πŸ€– Agent Architecture

The system is built around specialized AI agents that work together:

  1. Email Fetcher: Retrieves and processes incoming emails
  2. Email Analyzer: Analyzes email content and intent
  3. Reply Generator: Crafts context-aware email responses
  4. Newsletter Processor: Extracts valuable content from newsletters
  5. Post Formatter: Optimizes content for different social platforms
  6. Social Poster: Manages content distribution to social networks

πŸ“š Documentation

πŸ› οΈ Development

Running Tests

pytest

Code Style

This project uses:

  • Black for code formatting
  • isort for import sorting
  • Flake8 for linting

Run formatting and linting:

black .
isort .
flake8

πŸ“„ License

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

πŸ™ Acknowledgments

  • Built with FastAPI
  • Powered by CrewAI
  • Inspired by modern AI agent architectures

About

Before Google integrated Gemini into Google Workspace & Gmail, I built a multi-agent AI system using CrewAI, Flask, & React. Summarizes Gmail emails, generates replies with human review, extracts AI newsletters, & posts to X/LinkedIn. Customizable, scalable, & modern.

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