ForkReach
Multi-AI Marketing Agent for Indie Hackers

A conversational AI platform with specialized marketing agents for indie hackers and startups.
Powered by Google's Gemini AI for Twitter content, email marketing, landing pages & launch strategies.

Your AI-powered marketing team, available 24/7.

Getting started & staying tuned with us.

Star us, and you will receive all release notifications from GitHub without any delay!

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✨ Features

• 🤖 Specialized AI Agents - Purpose-built agents for different marketing tasks:

  • Twitter Agent - Generate engaging tweets and thread content
  • Email Marketing Agent - Craft compelling email campaigns
  • Landing Page Agent - Write converting landing page copy
  • Launch Strategist - Plan and execute product launches

• 🧠 Smart Routing - Auto-routes queries to the most appropriate agent based on user intent

• 💬 Real-time Streaming - Responses stream in real-time using the ai-sdk UI Message Stream Protocol

• 📦 Product Context - Personalize responses with your product/brand context

• 💾 Conversation History - Persist and continue conversations across sessions with Supabase

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🛠️ Tech Stack

Backend

• FastAPI - High-performance Python web framework
• Google Gemini AI - Powers all AI agents (gemini-2.5-flash, gemini-1.5-pro, etc.)
• Supabase - Database for conversation persistence
• UV - Modern Python package manager

Frontend

• Next.js 16 - React framework with App Router
• React 19 - Latest React with concurrent features
• Tailwind CSS 4 - Utility-first CSS framework
• Radix UI - Accessible component primitives
• ai-sdk - Vercel AI SDK for chat streaming
• Lucide React - Beautiful icon library

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🚀 Getting Started

Prerequisites

• Node.js v22.18.0+ (recommended via nvm)
• Python 3.13+
• UV package manager (pip install uv)
• Supabase account (for conversation persistence)

Environment Setup

Backend

Create a .env file in the backend/ directory:

GEMINI_API_KEY=your_gemini_api_key
SUPABASE_URL=your_supabase_url
SUPABASE_ANON_KEY=your_supabase_anon_key

Frontend

Create a .env.local file in the frontend/ directory:

NEXT_PUBLIC_API_URL=http://localhost:8000

Installation

Backend

cd backend
uv sync

Frontend

cd frontend
npm install

Running the Application

Start Backend Server

cd backend
uv run uvicorn main:app --reload

The API will be available at http://localhost:8000

Start Frontend Development Server

cd frontend
npm run dev

The app will be available at http://localhost:3000

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📁 Project Structure

├── backend/
│   ├── agents/                  # AI agent implementations
│   │   ├── base_agent.py        # Base agent class
│   │   ├── coordinator.py       # Agent routing coordinator
│   │   ├── twitter_agent.py     # Twitter content agent
│   │   ├── email_marketing_agent.py
│   │   ├── landing_page_agent.py
│   │   └── launch_strategist_agent.py
│   ├── main.py                  # FastAPI app entry point
│   ├── stream.py                # Streaming chat endpoint
│   ├── conversations_api.py     # Conversation CRUD API
│   ├── products_api.py          # Product context API
│   ├── supabase_client.py       # Supabase client setup
│   └── pyproject.toml           # Python dependencies
│
├── frontend/
│   ├── src/
│   │   ├── app/
│   │   │   └── session/         # Main chat session pages
│   │   ├── components/          # React components
│   │   │   └── ui/              # Shadcn UI components
│   │   └── contexts/            # React context providers
│   ├── public/                  # Static assets
│   └── package.json             # Node dependencies
│
└── README.md

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🔌 API Endpoints

Method	Endpoint	Description
POST	/api/chat	Stream chat responses from agents
GET	/api/agents	List available agents
GET	/api/conversations	Get user conversations
POST	/api/conversations	Create new conversation
POST	/api/conversations/{id}/messages	Add message to conversation
GET	/api/products	Get user products
POST	/api/products	Create product context

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📝 License

This project is licensed under the MIT License.

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🤝 Contributing

Contributions are welcome! Feel free to open issues and pull requests.