Project Info

Culturo

Inspiration

One of the ways that people going about learning about culture is by learning language. This is partially because that is probably the most streamlined way to do so and there are a plethora of resources for language learning. What we wanted to do is different. We want to give users an opportunity to learn to be a local whether that's by exploring the history, music, food, and landmarks from a country or by engaging in conversation with an agent to learn what its like to be a local.

What it does

WorldWise is an AI cultural immersion companion that delivers personalized snapshots via voice, visual content, and trivia. Voice-first interface — Engage in conversation with a Vapi Voice Agent to learn what it's like to be a local Cultural content feed — movies, news, music, restaurants, and attractions that make a country what it is Real-time trivia — dynamic questions from fetched content; stores memory about their user Agentic orchestration — Spotify, NewsAPI, Reddit, TripAdvisor, Wikipedia, Google Maps etc

How we built it

Frontend (React), Backend (Python/Flask), Multi-agent framework for coordinated workflows Asynchronous API integration with aiohttp, Health, orchestration, content feed, trivia, and voice endpoints Orchestrator routes user queries, ContentFeed agent gathers real-time data, TriviaAgent generates questions from content; Parallel API calls to reduce latency API integrations: Spotify (local music), NewsAPI (current events), Reddit (slang/community trends), TripAdvisor (restaurants, attractions), Deepgram (multilingual STT), Anthropic Claude Haiku (reasoning), Vapi (Voice AI)

Challenges we ran into

Integrating the sheer amount of APIs was difficult because each had different types of documentation + different hurdles to cross deepgram + Vapi was difficult because we were trying to include language support beyond just English; this required implementing a language detection script through deepgram and accordingly prompting vapi to respond in that language to come off as more personable ##

Accomplishments we're proud of

a working MVP for 3 cultures (Japan, Spanish, France) a solid intuitive front end with a content feed, trivia, and voice-first chatbot support for english, spanish, french, and japanese + scalable for other languages Letta Integration that remembers user progress; creates personalized experience for users; key for cultural immersion ##

What we learned

Technologies: Letta, Vapi, Deepgram, Claude While agentic workflows are always subjected to latency, there are ways to perform simultaneous processing to cut it down A voice first engagement approach makes it more accessible and personable for the user ##

What's next

Coming out with support for more cultures; our system is designed to be scalable (just have to fully build out the integrations) reducing latency with processing content and setting up the voice agent gathering feedback from users to see if there are other ways to deliver the culturally immersive experience we are passionate about

Cultura: Your Cultural Immersion Platformura

Cultura is a comprehensive cultural immersion application that provides rich, real-time content about countries including movies, news, music, food, attractions, and interactive trivia. All data is aggregated from multiple APIs and presented in an immersive UI

Features

Voice Interface (Vapi + Deepgram)

Speech recognition using Deepgram for voice input
Natural voice synthesis for responses
Real-time voice conversation about cultures and countries

Content Feed (News API, TripAdvisor API, Spotify API)

Movie cards with embedded YouTube trailers
News cards with current events and articles
Music cards with popular songs and Spotify integration
Food cards with local cuisine and restaurants
Attraction cards with landmarks and cultural sites

Interactive Trivia

Daily cultural quizzes for selected countries
Multiple choice questions with immediate feedback
Adaptive learning system that re-queues incorrect answers
Completion tracking and progress monitoring

Architecture

[User Selects Country]
   ↓
[Loading Screen with Country Facts]
   ↓
[Backend Orchestration] → [Multi-API Data Aggregation]
   ├── TMDB (Movie Trailers)
   ├── NewsAPI (Current Events)
   ├── Spotify (Music Playlists)
   ├── TripAdvisor (Food & Attractions)
   └── LLM Agents (Trivia Generation)
   ↓
[Country-Themed Snapshot Page]
   ├── Content Feed (Movies, News, Food, Attractions)
   ├── Interactive Trivia Panel
   └── Voice Assistant Interface

Tech Stack

Backend

Flask - Python web framework
Python 3.8+ - Async/await support
Deepgram - Speech-to-text transcription
Vapi - Voice assistant and TTS synthesis
Anthropic Claude - AI reasoning and content generation
TMDB - Movie trailer data
Spotify API - Music playlists and trending songs
NewsAPI - Current events and news
TripAdvisor API - Food and restaurant data
Agent-based architecture for content aggregation

Frontend

React
Styled Components - CSS-in-JS styling
Framer Motion - Smooth animations and transitions
Axios

Infrastructure

Agent Orchestrator - Coordinates multiple specialized agents
Deepgram Integration - Real-time speech recognition
Vapi Integration - Voice assistant capabilities
TMDB Integration - Movie and trailer data
Spotify Integration - Music discovery
NewsAPI Integration - Current events

Quick Start

Prerequisites

Python 3.8+
Node.js 16+
API keys for all services (see Configuration)

Backend Setup

Clone and navigate to backend:

cd backend

Install dependencies:

pip install -r requirements.txt

Configure environment variables:

cp env.example .env
# Edit .env with your API keys

Run the Flask server:

python app.py

Frontend Setup

Navigate to frontend:

cd frontend

Install dependencies:

npm install

Start the development server:

npm start

Open your browser:

http://localhost:3000

Configuration

Required API Keys

Create a .env file in the backend directory with the following keys:

# Voice & AI
DEEPGRAM_API_KEY=your_deepgram_api_key
VAPI_API_KEY=your_vapi_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key

# Music & Media
SPOTIFY_CLIENT_ID=your_spotify_client_id
SPOTIFY_CLIENT_SECRET=your_spotify_client_secret
NEWS_API_KEY=your_news_api_key
TMDB_API_KEY=your_tmdb_api_key

# Social & Cultural Data
REDDIT_CLIENT_ID=your_reddit_client_id
REDDIT_CLIENT_SECRET=your_reddit_client_secret

# Tourism & Attractions
TRIPADVISOR_API_KEY=your_tripadvisor_api_key

# Memory & Analytics
LETTA_API_KEY=your_letta_api_key

Getting API Keys

Deepgram - Sign up at https://deepgram.com/ for speech-to-text
Vapi - Get API key at https://vapi.ai/ for voice synthesis
Anthropic - Claude API at https://console.anthropic.com/ for AI reasoning
Spotify - Developer Dashboard at https://developer.spotify.com/ for music data
NewsAPI - Free tier at https://newsapi.org/ for news data
TMDB - Get API key at https://www.themoviedb.org/settings/api for movie trailers
Reddit - Reddit API at https://www.reddit.com/prefs/apps for cultural insights
TripAdvisor - Developer portal for food and attraction data

Example Usage

Voice Interaction

User: "Hey, I'm flying to Tokyo next week. Can you teach me the basics?"

Cultura: "Sure! In Japan, a polite greeting is 'Hajimemashite' — it means 'Nice to meet you.'
🇯🇵 The current government is a constitutional monarchy led by Prime Minister Fumio Kishida.
🍣 For food, locals love ramen alleys in Shinjuku and okonomiyaki in Osaka.
🎵 Here's what's trending on Spotify Japan: Fujii Kaze's 'Workin' Hard'.
🗣️ Slang tip: saying 'Yabai!' means 'That's crazy!' — good or bad.
Want to hear about festivals or how to behave at dinner?"

Key Features Explained

1. Voice-First Interface

Natural Conversation: Speak naturally, get cultural insights
Multilingual Support: Works in multiple languages
Real-time Processing: Instant cultural data aggregation

2. Cultural Intelligence

Comprehensive Data: Government, history, music, food, slang
Real-time Updates: Current news and trending topics
Authentic Sources: Reddit, Wikipedia, official APIs

3. Personalized Learning

Memory System: Remembers your interests and progress
Adaptive Content: Adjusts to your learning style
Cultural Quizzes: Interactive learning experiences

4. Observability

AI Tracing: Track AI reasoning and decision-making
Performance Metrics: Monitor accuracy and user engagement
Continuous Improvement: Data-driven enhancements

Development

Project Structure

lingua-cal-hacks/
├── backend/
│   ├── app.py              # Main Flask application
│   ├── integrations.py     # API integration classes
│   ├── requirements.txt    # Python dependencies
│   └── env.example        # Environment configuration
├── frontend/
│   ├── src/
│   │   ├── App.js         # Main React component
│   │   ├── App.css        # Styling
│   │   └── index.js       # Entry point
│   ├── package.json       # Node dependencies
│   └── public/            # Static assets
└── README.md              # This file

Deployment

Production Setup

Environment Configuration

export FLASK_ENV=production
export DATABASE_URL=postgresql://...
export REDIS_URL=redis://...

Acknowledgments

Anthropic - Claude AI for cultural reasoning
Deepgram - Multilingual speech recognition
Vapi - Voice interface platform
Spotify - Music data API
NewsAPI - News aggregation
Reddit - Cultural insights
Wikipedia - Historical data
Arize - AI observability platform

Contributors

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Technology

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AnthropicIn code
CSSIn code
FlaskIn code
HTMLIn code
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Codebase size

Source size

508 KB

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