Sohayb05/Yoruba_in

# Yoruba Dream Interpreter AI A lightweight, Vercel-ready web app that turns any dream description into a Yoruba spirituality-inspired interpretation. Users type a dream, submit, and receive symbol-based guidance pulled from Yoruba archetypes such as Oshun, Shango, Ogun, Oya, and more. ## Project Structure ``` . ├── api/ │ └── interpret.py # Python serverless handler (Vercel) ├── app.js # Frontend logic (fetch + UI state) ├── index.html # Minimalist UI markup ├── public/ # Static assets go here (empty placeholder) ├── styles.css # Yoruba-inspired styling └── vercel.json # Runtime configuration (Python 3.11) ``` ## Requirements - Node.js 18+ (for running `vercel dev` locally) - Python 3.11 runtime provided by Vercel (no local Python dependency needed unless you want to run tests) - Vercel CLI (`npm i -g vercel`) for local dev or deployment ## Local Development 1. **Install dependencies (only Vercel CLI needed)** ```bash npm install -g vercel ``` 2. **Start the dev server** ```bash cd /Users/macbook/Desktop/chatbot vercel dev ``` - Frontend served at `localhost` - API endpoint lives at `localhost` 3. **Use the app** - Open the local URL, enter any dream text, click **Interpret dream**. - The UI shows a loader while waiting and renders the interpretation response. ## Deployment (Vercel) 1. Log in (first time only): ```bash vercel login ``` 2. From the project root: ```bash vercel deploy --prod ``` Vercel auto-detects the frontend and Python serverless function using `vercel.json` and builds a globally distributed deployment. ## API Details - **Endpoint**: `POST /api/interpret` - **Payload**: ```json { "dream": "I was walking through a forest as lightning struck" } ``` - **Response**: ```json { "interpretation": "In Yoruba spirituality..." } ``` - Logic: keyword extraction → map to Yoruba archetypes → craft narrative. Missing keywords fall back to a gen …