Prompt to Signature

A full-stack application for generating custom signatures from text prompts using AI models. DSPy program implmentation here: https://www.modaic.dev/fadeleke/prompt-to-signature

Quickstart

Prerequisites

• Node.js (v18 or higher)
• Python 3.11+
• uv (Python package manager)
• Make

1. Environment Setup

Server Environment Variables

Create a .env file in the server/ directory:

cd server
cp .env.example .env

Edit server/.env and add your API keys:

MODAIC_TOKEN="your-modaic-token-here"
GEMINI_API_KEY="your-gemini-api-key-here"
OPENAI_API_KEY="your-openai-api-key-here"
OPENROUTER_API_KEY="your-openrouter-api-key-here"
API_URL="http://localhost:8000"
CLIENT_URL="http://localhost:3000"

Note on API Keys: The API key you need depends on which model you're using:

• Default: The application uses openrouter/claude-haiku-4.5, so you'll need to set OPENROUTER_API_KEY
• Custom Model: You can override the model in server/main.py:29 by passing config_options:

  AutoAgent.from_precompiled(
      "fadeleke/prompt-to-signature",
      config_options={"lm": "openai/gpt-4o"}
  )

  In this case, you would need to set OPENAI_API_KEY instead.

Client Environment Variables

Create a .env file in the client/ directory:

cd client
cp .env.example .env

Edit client/.env and set the API URL:

NEXT_PUBLIC_API_URL="http://localhost:8000"

2. Install Dependencies

Frontend Dependencies

cd client
npm install

Backend Dependencies

cd server
uv sync

3. Run the Application

From the root directory, you can use the following commands:

Start Both Services

make start-all

Start Services Individually

# Start frontend only
make start-frontend

# Start backend only
make start-backend

Stop Services

# Stop both services
make stop-all

# Stop frontend only
make stop-frontend

# Stop backend only
make stop-backend

4. Access the Application

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000

Tech Stack

• Frontend: Next.js, React, TypeScript
• Backend: FastAPI, Python
• AI Models: Modaic, Gemini, OpenAI