Product Launch Assistant

A comprehensive AI-powered product launch planning tool that generates market research, pricing strategies, launch plans, and marketing content using advanced AI workflows.

📸 Application Screenshots

Product Input Form

Clean, intuitive interface for entering your product details. The form guides you through providing essential information about your product, features, and target market.

AI-Generated Results

Comprehensive launch plan with tabbed sections for market research, product descriptions, pricing strategies, launch plans, and marketing content. Each section provides actionable insights tailored to your specific product.

🚀 Features

• 🤖 AI-Powered Analysis: Uses LangGraph workflow with DigitalOcean's Inference API
• 📊 Comprehensive Planning: Generates 5 key sections for product launch
• 🎨 Modern UI: Beautiful, responsive React interface with step-by-step workflow
• 📱 Mobile Friendly: Works seamlessly on desktop and mobile devices
• 🔄 2-Component Architecture: Scalable frontend/backend separation for DigitalOcean App Platform
• 📋 Export Options: Download your complete launch plan
• 🔍 Interactive Results: Tabbed interface with copy-to-clipboard functionality

🎯 What You Get

The AI generates a comprehensive launch strategy including:

1. 📈 Market Research

   • Competitive landscape analysis
   • Market size and opportunities
   • SWOT analysis
   • Key trends and recommendations

2. 📝 Product Description

   • E-commerce optimized copy
   • Key features and benefits
   • Target audience messaging
   • Compelling value propositions

3. 💰 Pricing Strategy

   • Multi-tier pricing structure
   • Cost analysis and margins
   • Competitive positioning
   • Revenue projections

4. 🗓️ Launch Plan

   • Pre-launch, launch, and post-launch phases
   • Week-by-week action items
   • Success metrics and KPIs
   • Risk mitigation strategies

5. 📢 Marketing Content

   • Social media posts
   • Email campaigns
   • Press release templates
   • Influencer collaboration briefs

🏗️Project Structure

product-launch-assistant/
├── frontend/                   # React application
│   ├── src/
│   │   ├── components/         # UI components
│   │   ├── App.js             # Main app component
│   │   └── index.js           # Entry point
│   ├── screenshots/           # Application screenshots
│   │   ├── form.png          # Product input form
│   │   └── results.png       # Generated results
│   ├── package.json
│   └── Dockerfile            # Frontend container
├── backend/                   # FastAPI application  
│   ├── main.py               # API server with LangGraph workflow
│   ├── requirements.txt      # Python dependencies
│   └── Dockerfile           # Backend container
├── app.yaml                 # DigitalOcean App Platform config
└── README.md               # This file

🚀 Quick Start

Local Development

1. Backend Setup:

   cd backend/
   
   #create virtual environment
   python -m venv venv
   
   #use the virtual environment
   source venv/bin/activate
   
   pip install -r requirements.txt
   
   # Copy and configure environment variables
   cp .env.example .env
   # Edit .env and set the following keys with your actual values
   # - DIGITALOCEAN_INFERENCE_KEY (required)
   # - SERPER_API_KEY (recommended for live web search)
   
   # Start backend
   python main.py

2. Frontend Setup (new terminal):

   cd frontend/
   npm install
   
   # Create .env file  
   echo "REACT_APP_API_URL=http://localhost:8000" > .env
   
   # Start frontend
   npm start

3. Access the application:

   • Frontend: http://localhost:3000
   • API Docs: http://localhost:8000/docs
   • Health Check: http://localhost:8000/health

🚢 DigitalOcean App Platform Deployment

Manual Setup

1. Create App in DigitalOcean App Platform
2. Connect Repository and configure 2 services:

Backend Service:

• Name: backend
• Source Directory: /backend
• Environment: Python
• Run Command: python main.py
• Port: 8000
• Routes: /backend
• Environment Variables:

  DIGITALOCEAN_INFERENCE_KEY = [your_key] (SECRET)
  SERPER_API_KEY = [your_serper_key] (SECRET)
  

Frontend Service:

• Name: frontend
• Source Directory: /frontend
• Environment: Node.js
• Build Command: npm run build
• Run Command: npx serve -s build -l 3000
• Port: 3000
• Routes: / (catch-all)
• Environment Variables:

  REACT_APP_API_URL = [update_with_backend_url_once_deployed]
  If you are deploying using "Deploy with DO" button click, this step is not required.
  

3. Deploy and your app will be live with 2 independent services!

📋 API Usage

Generate Launch Plan

Endpoint: POST /backend/launch_assistant

Example Request:

{
  "product_name": "Trendy tote bags with bold designs and Gen Z slogans",
  "product_details": "Trendy tote bags made from eco-friendly materials, featuring bold graphics and Gen Z-inspired slogans. Durable, stylish, and perfect for everyday use.",
  "target_market": "Gen Z teens and young adults who love fashion, self-expression, and pop culture trends."
}

Response Structure:

{
  "product_name": "Smart Fitness Mirror",
  "product_details": "...",
  "target_market": "...",
  "market_research": "AI-generated market analysis...",
  "product_description": "Compelling e-commerce copy...",
  "pricing_strategy": "Strategic pricing recommendations...",
  "launch_plan": "Step-by-step launch timeline...",
  "marketing_content": "Social media and email content..."
}

🤖 AI Model Recommendations

Based on testing, these models have delivered good results:

• llama3.3-70b-instruct - Great balance of quality and cost
• openai-gpt-4o - Best quality, higher cost

Configure in backend/main.py by updating the model parameter.

🔗 Links

• DigitalOcean Inference API: Documentation
• LangGraph: Framework Documentation