⚡ Prompt Architect

A professional, full-stack monorepo application designed to evaluate and optimize AI prompts using the Google Gemini 3 API. This tool transforms raw drafts into highly-engineered instructions while providing real-time telemetry on cost, latency, and token consumption.

🚀 Key Features

• Intelligent Optimization: Uses state-of-the-art reasoning to restructure prompts for clarity and persona.
• Analysis Dashboard: Provides a numerical score (0-100) across four dimensions: Clarity, Context, Constraints, and Persona.
• Real-time Telemetry: Instant feedback on API latency, token counts, and estimated USD cost.
• Creative Control: Adjust model temperature and strategy (Logical, Creative, or Concise) via a unified UI.
• Developer Export: One-click Python code snippets to integrate optimized prompts into your own apps.
• Dockerized Architecture: Modern microservice setup with separate Backend (FastAPI) and Frontend (React) containers.

📂 Project Structure

prompt-optimizer/
├── .gitignore               # Root-level Git exclusions
├── docker-compose.yml       # Orchestrates Backend & Frontend
├── README.md                # Project documentation
├── backend/                 # FastAPI Microservice
│   ├── main.py              # Core Logic & Gemini Integration
│   ├── Dockerfile           # Python Container Definition
│   ├── requirements.txt     # Backend Dependencies
│   └── .env                 # API Keys (DO NOT COMMIT)
└── frontend/                # React + Vite + Tailwind SPA
    ├── src/
    │   ├── App.jsx          # UI Logic & Streaming Handling
    │   └── main.jsx         # Entry Point
    ├── Dockerfile           # Nginx/Node Container Definition
    └── package.json         # Node Dependencies

🛠️ Tech Stack

Backend: Python 3.10+, FastAPI, Google GenAI SDK. Frontend: React (Vite), Tailwind CSS, Headless UI. Observability: LangSmith (Optional tracing support). DevOps: Docker, Nginx.

🚦 Getting Started

1. Prerequisites * Docker Desktop * Google Gemini API Key

2. Environment Configuration Create a .env file inside the backend/ directory:

GEMINI_API_KEY=<your_actual_key_here>

3. Running with Docker (Recommended)

docker compose up --build

• UI: http://localhost:3000
• API: http://localhost:8000/docs

4. Local Development (Manual)

Backend:

cd backend
pip install -r requirements.txt
python main.py

Frontend:

cd frontend
npm install
npm run dev