# Project export: Remixify

This document was generated by HackStack to give an AI agent context about a hackathon project. Sections are labeled with their provenance; content marked as truncated was cut to keep this document small.

## Project metadata

- Hackathon: Cal Hacks 12.0
- Tagline: Don't scroll Reels, scroll Remixify.
- Devpost: https://devpost.com/software/remixify
- GitHub: https://github.com/nidhigaonkar/calhacks25
- Video: https://www.youtube.com/embed/3p9rziCgl7s?enablejsapi=1&hl=en_US&rel=0&start=&version=3&wmode=transparent
- Result: winner ([MLH] Best Use of Gemini API)
- Team: 3 GitHub contributor(s) — Nidhi Gaonkar (47 commits), sidv1711 (16 commits), Claude (2 commits)

## Devpost submission (written by the team)

### Overview

✨

### Inspiration

Remixify revolutionizes the way users interact with companies to create a better and more engaging experience for viewers. Remixify was inspired by the growing need for brands to create more engaging, personalized, and data-driven advertising content. We also thought it'd be really funny to edit videos and images with AI for people to explore their creativity and have fun collaborating together. The main idea for our app is that: Advertisers rarely know what consumers wish their ads looked like or what made their ad so viral beyond surface-level metrics Creative users, especially young creators, want a way to express themselves, win rewards, and actually be heard by the brands they engage with. Remixify creates a platform where creativity and product discovery meet.

### What it does

Remixify is an innovative platform that transforms traditional advertising into an interactive, fun, community-driven experience. Users can also scroll a feed of real ads and remix them using advanced AI image and video generation (fully Gemini powered!), with style presets and creative prompts, for example, “Add a cat mascot” or “turn the sky to night”. User can share, earn likes, comments & win brand-sponsored rewards based on the remixes they make. Users can also upload an image, and we use Gemini to label and tag the company automatically. Remixify then provides real-time insights into ad performance, audience engagement, and creative trends using Letta's Deep Research Agents to extract insights from every remix + interaction, and memory blocks that accumulate key information such as: Most remixed ad elements and which remixes improve engagement or virality And organize all this information into an Analytics page, so companies finally see what people actually want, including specific information about demographics, top aesthetics, and more. Finally, we help predict ad performance through Signal Extraction. We built a model to analyze user behavior (prompts summarized by Claude), commenting patterns, and performance metrics to provide actionable insights for the company. For example, we extract context clues like references to TikTok, Instagram, or specific trends to see platforms that users are most active on to target ad spend. 🛠️ How We Built It Tech stack: Frontend: Next.js for the web application framework Tailwind CSS for styling Shadcn UI components for a modern, accessible interface TypeScript Backend & AI: Supabase for database and authentication Custom API routes for handling image generation and analysis Integration with Google's Gemini API extensively for image editing (Nano Banana 🍌) Integration with Google’s Veo3 for video editing Real-time data processing for analytics and signal extraction Analytics: Custom analytics engine (Letta) for user insights and analytics Claude for creative insights and trend analysis Real-time performance metrics and behavioral pattern recognition Opportunities for Conversion integration to automatically reach out to leads. Letta Deep Research Agents Integration: We use Letta’s agents and their Memory Blocks to track: Most remixed ad elements Popular user modifications Letta Deep Research Agents extract overall sentiments and advice, helping brands understand how users feel about the brand as a whole Which remixes improve engagement or virality 🧗 Challenges We Ran Into Real-time Video and Image Generation: Implementing fast and reliable AI-powered image generation while maintaining quality and brand consistency. Although calling the API for video generation was not that difficult, it was very hard to get it to maintain the same theme as the original video as well as ensure that the generation didn't take too long. Performance Optimization: Handling large-scale data processing for analytics while maintaining a responsive UI. Making the comments hierarchical so people's edits could affect each other was a little bit difficult since we had to handle storing data in Supabase and pulling it very quickly in order to apply different comments. Data Analysis: Building Letta Agents with Deep Research and Memory Blocks to extract meaningful signals from user behavior and ad performance, not just noise. Overall, we coordinating multiple AI services and ensuring seamless communication between frontend and backend was pretty difficult but we got it to work.

### Accomplishments we're proud of

Built a sophisticated AI-powered creative platform in a short timeframe Created an intuitive and engaging user interface for complex features and a full-fledged social platform. Implemented advanced analytics with real-time analysis. Successfully integrated multiple AI models for different aspects of the platform in a way that is invisible but still valuable to the user.

### What we learned

We learned more about real-time Analytics, especially how to process and visualize large amounts of data efficiently. We also focused a lot on user experience and design, and discovered how to make complex features accessible to users in a way that was easy to understand. Prompt engineering is critical: Specificity, tone, and structure determine the output, especially for the video models. Design matters: We spent time creating chat panes, responsive cards, and leaderboards, all small things that made the platform intuitive and engaging.

### What's next

Our main idea is to expand from just ads and provide a platform where users can remix and create funny videos and photos, but also maintain this idea of campaigns, where companies can incentivize users to remix their specific ads by providing prizes. We also want: Bettter Analytics: more detailed audience segmentation and possibly suggestions for the company to figure out where/who to market to, or creating marketing assets just from these analytics. Expansion into mobile app form to better reflect TikTok or Instagram feeds, as well as API access for third-party integrations (ex: Download video of a TikTok and remix that), support for more ad formats and platforms

## README (from the GitHub repository)


## Remixify - Ad Remix Platform - CalHacks 2025

Welcome to Remixify, an exciting social platform for brands to upload ads and let users create remixes through prompt-based AI editing. Includes image editing via Gemini, video generation via Veo 3, user comment/prompt analysis via Claude, deep research, memory, and analytics about the company via Letta, and storage/database via Supabase.

## Tech Stack

- **Frontend**: Next.js 16, React 19, Tailwind
- **APIs**: Next.js Route Handlers under `frontend/app/api/*`
- **AI services**:
  - Image editing: Google Gemini 2.5 Flash Image
  - Video generation: Vertex AI Veo 3.1 (preview)
  - Prompt analysis: Anthropic Claude
  - Analytics: Letta Agent API
- **Data**: Supabase (Postgres + Storage)
- **Machine Learning**: 

## Setup

### Prerequisites

- Node.js 18.18+ and pnpm
- A Supabase project with:
  - Database tables described below
  - A public storage bucket named `ads`
- API keys/accounts for the services you want to enable (Gemini, Claude, Google Cloud/Vertex AI, Letta)

### Environment Variables

Create a `.env.local` (or `.env`) file in the `frontend` directory with at least:

```env
# Supabase (required)
NEXT_PUBLIC_SUPABASE_URL=your-supabase-project-url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your-supabase-anon-key

# Image editing (Gemini)
GEMINI_API_KEY=your-gemini-api-key

# Prompt analysis (Claude)
CLAUDE_API_KEY=your-claude-api-key

# Video generation (Vertex AI Veo) – choose ONE auth method
# 1) Short-lived OAuth token (local dev)
GCP_PROJECT_ID=your-gcp-project-id
GCP_ACCESS_TOKEN=ya29....   # 'gcloud auth print-access-token' (expires ~1h)

# OR 2) Service Account JSON (recommended). If you choose this, set the file path and update your code to use ADC:
# GOOGLE_APPLICATION_CREDENTIALS=./service-account-key.json

# Letta for analytics from the web
LETTA_API_KEY=your-letta-api-key
# Optional overrides:
# LETTA_BASE_URL=https://api.letta.ai
# LETTA_AGENT_ID=agent-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
```

### Database Setup (Supabase)

Run the SQL in your Supabase SQL editor from your existing README to create the base tables. The app expects these tables/columns at runtime:

- companies
  - id (uuid, pk)
  - name (text)
  - created_at (timestamptz, default now)

- ads
  - id (uuid, pk)
  - company_id (uuid, fk → companies.id)
  - title (text)
  - image_url (text, optional if video)
  - video_url (text, optional)
  - location (text, used by UI)
  - likes (int, used by UI; code initializes a random value if not provided)
  - created_at (timestamptz, default now)

- prompts
  - id (uuid, pk)
  - ad_id (uuid, fk → ads.id)
  - user_id (uuid or string; code auto-generates a stable browser id if not uuid)
  - content (text)
  - parent_id (uuid, nullable; threaded replies)
  - edited_image_url (text, optional)
  - edited_video_url (text, optional; if not present, the app falls back to saving video URLs in `edited_image_url`)
  - created_at (timestamptz, default now)

Seed data:
- Use `supabase-test-data.sql` at repo root to insert Nike sample data.

Storage:
- Create a public bucket named `ads`. The app writes under:
  - `images/` and `videos/` (uploads)
  - `edited/` and `edited-videos/` (generated assets)

### Installation & Running

```bash
cd frontend
pnpm install
pnpm dev
# open http://localhost:3000
```

## Features

- **Ad Upload**: Image/video uploads saved to Supabase Storage and `ads` table.
- **AI-Powered Remixing**:
  - Image edits with Gemini using your prompt + original image.
  - Video generation with Vertex AI Veo from first/last frames and prompt.
- **Prompt Analysis**: Aggregates user prompts and analyzes with Claude.
- **Analytics Dashboard**: Letta agent returns brand analytics JSON for visualization. Letta deep memory and research analytics sourced from the web.
- **Threads/Replies**: Users can reply to prompts (`parent_id`) to build remix chains.
- **Feed**: Mix of mock ads and Supabase ads; supports likes, comments count, search, and deletion of user uploads.







## Detected evidence (automated analysis)

Indexed codebase: 45 recognized source files, 457 KB.
- CSS (language) — detected in the code
- Google Gemini (technology) — detected in the code
- Next.js (technology) — detected in the code
- OpenAI (technology) — detected in the code
- React (technology) — detected in the code
- SQL (language) — detected in the code
- Supabase (technology) — detected in the code
- Tailwind CSS (technology) — detected in the code
- TypeScript (language) — detected in the code
- JavaScript (language) — claimed on Devpost, not found in the code
- Python (language) — claimed on Devpost, not found in the code
- AI coding agent: Claude Code — evidence: commit authorship or trailers

## Codebase structure (from repository index)

### Files (54 of 54)

```
.DS_Store
.gitignore
frontend/.gitignore
frontend/app/ad/[id]/page.tsx
frontend/app/api/analyze-prompts/route.ts
frontend/app/api/edit-image/route.ts
frontend/app/api/edit-video/route.ts
frontend/app/api/letta-analytics/route.ts
frontend/app/api/upload/route.ts
frontend/app/brands/analytics-dashboard.tsx
frontend/app/brands/page.tsx
frontend/app/brands/signal-extraction.tsx
frontend/app/challenges/page.tsx
frontend/app/globals.css
frontend/app/layout.tsx
frontend/app/leaderboard/page.tsx
frontend/app/page.tsx
frontend/app/profile/page.tsx
frontend/components.json
frontend/components/ad-card.tsx
frontend/components/comment-input.tsx
frontend/components/navigation.tsx
frontend/components/remix-modal.tsx
frontend/components/theme-provider.tsx
frontend/components/ui/avatar.tsx
frontend/components/ui/badge.tsx
frontend/components/ui/button.tsx
frontend/components/ui/card.tsx
frontend/components/ui/dialog.tsx
frontend/components/ui/input.tsx
frontend/components/ui/label.tsx
frontend/components/ui/progress.tsx
frontend/components/ui/tabs.tsx
frontend/components/ui/textarea.tsx
frontend/components/upload-ad-modal.tsx
frontend/docs/conversion-integration-guide.md
frontend/lib/conversion-tracking.ts
frontend/lib/supabase.ts
frontend/lib/types.ts
frontend/lib/utils.ts
frontend/lib/videoUtils.ts
frontend/next.config.mjs
frontend/package.json
frontend/postcss.config.mjs
frontend/README.md
frontend/styles/globals.css
frontend/tsconfig.json
LETTA_CURRENT_CONFIG.md
package.json
README.md
scripts/get-analytics.mjs
scripts/run-letta-agent.mjs
SUPABASE_SETUP.md
supabase-test-data.sql
```

### Dependencies

- frontend/package.json: @google/generative-ai@^0.24.1, @hookform/resolvers@^3.10.0, @letta-ai/letta-client@^0.0.68665, @radix-ui/react-accordion@1.2.2, @radix-ui/react-alert-dialog@1.1.4, @radix-ui/react-aspect-ratio@1.1.1, @radix-ui/react-avatar@1.1.2, @radix-ui/react-checkbox@1.1.3, @radix-ui/react-collapsible@1.1.2, @radix-ui/react-context-menu@2.2.4, @radix-ui/react-dialog@1.1.4, @radix-ui/react-dropdown-menu@2.1.4, @radix-ui/react-hover-card@1.1.4, @radix-ui/react-label@2.1.1, @radix-ui/react-menubar@1.1.4, @radix-ui/react-navigation-menu@1.2.3, @radix-ui/react-popover@1.1.4, @radix-ui/react-progress@1.1.1, @radix-ui/react-radio-group@1.2.2, @radix-ui/react-scroll-area@1.2.2, @radix-ui/react-select@2.1.4, @radix-ui/react-separator@1.1.1, @radix-ui/react-slider@1.2.2, @radix-ui/react-slot@1.1.1, @radix-ui/react-switch@1.1.2, @radix-ui/react-tabs@1.1.2, @radix-ui/react-toast@1.2.4, @radix-ui/react-toggle@1.1.1, @radix-ui/react-toggle-group@1.1.1, @radix-ui/react-tooltip@1.1.6, @supabase/supabase-js@^2.76.1, @tailwindcss/postcss@^4.1.9, @types/node@^22, @types/react@^19, @types/react-dom@^19, @vercel/analytics@latest, autoprefixer@^10.4.20, class-variance-authority@^0.7.1, clsx@^2.1.1, cmdk@1.0.4, date-fns@4.1.0, embla-carousel-react@8.5.1, input-otp@1.4.1, lucide-react@^0.454.0, next@16.0.0, next-themes@^0.4.6, postcss@^8.5, react@19.2.0, react-day-picker@9.8.0, react-dom@19.2.0, react-hook-form@^7.60.0, react-resizable-panels@^2.1.7, recharts@2.15.4, sonner@^1.7.4, tailwind-merge@^2.5.5, tailwindcss@^4.1.9, tailwindcss-animate@^1.0.7, tw-animate-css@1.3.3, typescript@^5, vaul@^0.9.9, zod@3.25.76
- package.json: @letta-ai/letta-client@^0.0.68665, @supabase/supabase-js@^2.76.1, dotenv@^17.2.3, exa-js@^1.10.2, openai@^6.7.0

### Recent commits (newest first)

- Revise README introduction for clarity
- final edits
- Merge remote-tracking branch 'origin/main'
- Save current work before merge
- Merge branch 'main' of https://github.com/nidhigaonkar/calhacks25
- starting conversion stuff
- Merge remote-tracking branch 'origin/main'
- Extensive front-end designs, video generation fixed.
- analytics and signal intelligence
- Clarify Letta feature description in README
- Revise README for feature and API updates
- Revise README for project rebranding and details
- veo3 video generation functional in chat
- bigger upload btn, ad description updates
- Merge remote-tracking branch 'origin/main'
- ui fixes
- Fix Supabase error handling for graceful degradation
- deleted mock
- Add edited_image_url column to prompts table and update test data
- Merge branch 'main' of https://github.com/nidhigaonkar/calhacks25

## Key source files (fetched from GitHub, selected and truncated for size)

### SUPABASE_SETUP.md

```markdown
# Supabase Storage Setup

To ensure images render correctly, you need to make your Supabase storage bucket public:

## Steps:

1. Go to your Supabase Dashboard
2. Navigate to **Storage** in the left sidebar
3. Find the `ads` bucket
4. Click on the bucket settings (three dots or gear icon)
5. Make sure the bucket is set to **Public**
6. Set the following policies:

### Storage Policies:

Go to **Storage** > **Policies** > **ads bucket** and ensure these policies exist:

#### Policy 1: Public Access (SELECT)
```sql
CREATE POLICY "Public Access"
ON storage.objects FOR SELECT
USING ( bucket_id = 'ads' );
```

#### Policy 2: Allow Uploads (INSERT)
```sql
CREATE POLICY "Allow uploads"
ON storage.objects FOR INSERT
WITH CHECK ( bucket_id = 'ads' );
```

#### Policy 3: Allow Deletes (DELETE)
```sql
CREATE POLICY "Allow deletes"
ON storage.objects FOR DELETE
USING ( bucket_id = 'ads' );
```

## Verify Setup:

After setting up the policies, try:
1. Upload a new file through your app
2. Copy the returned URL from the console
3. Paste it in a new browser tab - it should load the image
4. If it doesn't load, the bucket might not be public or policies are incorrect

## Alternative: Check via Supabase CLI

You can also check if the bucket exists:
```bash
# List all buckets
npx supabase storage ls

# Check if 'ads' bucket exists and is public
```

If the bucket doesn't exist, create it:
```sql
-- Run this in your Supabase SQL Editor
INSERT INTO storage.buckets (id, name, public)
VALUES ('ads', 'ads', true);
```

```

### LETTA_CURRENT_CONFIG.md

```markdown
# Letta Current Configuration

## 🎯 Current Company Being Analyzed

**Nike** - All Letta analytics are currently configured to analyze Nike advertising campaigns.

## 📊 What Letta is Analyzing

Your Letta agent generates analytics for:
- **Sentiment Analysis** - How audiences feel about Nike ads (positive/neutral/negative)
- **Audience Demographics** - Age groups, gender distribution, and geographic locations of Nike ad viewers
- **Competitor Benchmarking** - How Nike's campaign performance compares to competitors like Adidas, Puma, and Under Armour

## 🏷️ "Powered by Letta" Badges

All Letta-powered components now display a badge:
- ✅ Sentiment Analysis card
- ✅ Audience Demographics card
- ✅ Competitor Benchmarking card

## 🔄 Changing the Company

To analyze a different company, edit these files:

### 1. API Route (`frontend/app/api/letta-analytics/route.ts`)
Line 18:
```typescript
Please analyze [COMPANY NAME] advertising campaign data and provide analytics in JSON format.
```

### 2. Test Script (`scripts/get-analytics.mjs`)
Line 25:
```typescript
Please analyze the [COMPANY NAME] advertising campaign and provide detailed analytics data in JSON format.
```

### Example: Switching to Apple
Replace "Nike" with "Apple" in both locations, then:
```bash
node scripts/get-analytics.mjs  # Test the change
npm run dev                      # Restart your app
```

## 📍 Current Status

✅ **Active Company:** Nike
✅ **Letta API Key:** Configured in `frontend/.env`
✅ **Agent ID:** agent-3af75001-7e1e-4029-a63a-2cabb24d34fd
✅ **Badges Added:** All analytics components
✅ **Test Working:** Successfully generates realistic data

## 🎨 Badge Design

The "Powered by Letta" badge includes:
- ✨ Sparkles icon
- Outline variant styling
- Small text size (text-xs)
- Positioned in card headers

## 💡 Data Source

Letta generates **simulated analytics** based on:
- Industry knowledge of Nike campaigns
- Typical performance benchmarks
- Realistic demographic distributions
- Competitor market positions

The data is realistic but not live-scraped. For real-time data, you would need to configure custom Letta tools to scrape actual social media APIs.

```

### package.json

```
{
  "dependencies": {
    "@letta-ai/letta-client": "^0.0.68665",
    "@supabase/supabase-js": "^2.76.1",
    "dotenv": "^17.2.3",
    "exa-js": "^1.10.2",
    "openai": "^6.7.0"
  }
}

```

### frontend/package.json

```
{
  "name": "my-v0-project",
  "version": "0.1.0",
  "private": true,
  "scripts": {
    "build": "next build",
    "dev": "next dev",
    "lint": "eslint .",
    "start": "next start"
  },
  "dependencies": {
    "@google/generative-ai": "^0.24.1",
    "@hookform/resolvers": "^3.10.0",
    "@letta-ai/letta-client": "^0.0.68665",
    "@radix-ui/react-accordion": "1.2.2",
    "@radix-ui/react-alert-dialog": "1.1.4",
    "@radix-ui/react-aspect-ratio": "1.1.1",
    "@radix-ui/react-avatar": "1.1.2",
    "@radix-ui/react-checkbox": "1.1.3",
    "@radix-ui/react-collapsible": "1.1.2",
    "@radix-ui/react-context-menu": "2.2.4",
    "@radix-ui/react-dialog": "1.1.4",
    "@radix-ui/react-dropdown-menu": "2.1.4",
    "@radix-ui/react-hover-card": "1.1.4",
    "@radix-ui/react-label": "2.1.1",
    "@radix-ui/react-menubar": "1.1.4",
    "@radix-ui/react-navigation-menu": "1.2.3",
    "@radix-ui/react-popover": "1.1.4",
    "@radix-ui/react-progress": "1.1.1",
    "@radix-ui/react-radio-group": "1.2.2",
    "@radix-ui/react-scroll-area": "1.2.2",
    "@radix-ui/react-select": "2.1.4",
    "@radix-ui/react-separator": "1.1.1",
    "@radix-ui/react-slider": "1.2.2",
    "@radix-ui/react-slot": "1.1.1",
    "@radix-ui/react-switch": "1.1.2",
    "@radix-ui/react-tabs": "1.1.2",
    "@radix-ui/react-toast": "1.2.4",
    "@radix-ui/react-toggle": "1.1.1",
    "@radix-ui/react-toggle-group": "1.1.1",
    "@radix-ui/react-tooltip": "1.1.6",
    "@supabase/supabase-js": "^2.76.1",
    "@vercel/analytics": "latest",
    "autoprefixer": "^10.4.20",
    "class-variance-authority": "^0.7.1",
    "clsx": "^2.1.1",
    "cmdk": "1.0.4",
    "date-fns": "4.1.0",
    "embla-carousel-react": "8.5.1",
    "input-otp": "1.4.1",
    "lucide-react": "^0.454.0",
    "next": "16.0.0",
    "next-themes": "^0.4.6",
    "react": "19.2.0",
    "react-day-picker": "9.8.0",
    "react-dom": "19.2.0",
    "react-hook-form": "^7.60.0",
    "react-resizable-panels": "^2.1.7",
    "recharts": "2.15.4",
    "sonner": "^1.7.4",
    "tailwind-merge": "^2.5.5",
    "tailwindcss-animate": "^1.0.7",
    "vaul": "^0.9.9",
    "zod": "3.25.76"
  },
  "devDependencies": {
    "@tailwindcss/postcss": "^4.1.9",
    "@types/node": "^22",
    "@types/react": "^19",
    "@types/react-dom": "^19",
    "postcss": "^8.5",
    "tailwindcss": "^4.1.9",
    "tw-animate-css": "1.3.3",
    "typescript": "^5"
  }
}

```

### frontend/app/layout.tsx

```typescript
import type React from "react"
import type { Metadata } from "next"
import { Inter, Permanent_Marker } from "next/font/google"
import { Analytics } from "@vercel/analytics/next"
import Script from "next/script"
import "./globals.css"
import { Navigation } from "@/components/navigation"

const inter = Inter({
  subsets: ["latin"],
  weight: ["400", "500", "600", "700", "800", "900"],
  variable: "--font-inter",
})

const marker = Permanent_Marker({
  weight: "400",
  subsets: ["latin"],
  variable: "--font-marker",
})

export const metadata: Metadata = {
  title: "Remixify - Turn Customers Into Your Creative Team",
  description: "A social platform where users remix and recreate ads using AI",
  generator: "v0.app",
}

export default function RootLayout({
  children,
}: Readonly<{
  children: React.ReactNode
}>) {
  return (
    <html lang="en">
      <head>
        <Script src="https://p.conversion.ai" strategy="afterInteractive" />
      </head>
      <body className={`font-sans antialiased`}>
        <Navigation />
        {children}
        <Analytics />
      </body>
    </html>
  )
}

```

### frontend/app/page.tsx

```typescript
"use client"

import { useState, useEffect } from "react"
import { useRouter } from "next/navigation"
import { Button } from "@/components/ui/button"
import { Card } from "@/components/ui/card"
import { Avatar, AvatarFallback, AvatarImage } from "@/components/ui/avatar"
import { RemixModal } from "@/components/remix-modal"
import { UploadAdModal } from "@/components/upload-ad-modal"
import { Heart, MessageCircle, Sparkles, Bookmark, MoreHorizontal, Upload, Trash2, ChevronDown } from "lucide-react"
import { saveAd, getOrCreateCompany, getAllAds, deleteAd } from "@/lib/supabase"

const categories = ["All", "Super Bowl", "Tech", "Viral", "Fashion", "Food"]

const mockAds = [

  {
    id: 2,
    brand: "Apple",
    location: "Cupertino, California",
    image: "/apple-iphone-product-advertisement.jpg",
    caption: "Innovation that moves the world forward. Beautifully designed, simply powerful.",
    remixCount: 2891,
    likes: 5234,
    isLiked: false,
    comments: 289,
    category: "Tech",
    topComments: [
      { user: "tech_enthusiast", text: "Can't wait to remix this!", likes: 67 },
      { user: "designer_emma", text: "The minimalism is stunning", likes: 52 },
    ],
  },
  {
    id: 4,
    brand: "Tesla",
    location: "Austin, Texas",
    image: "/tesla-electric-car-advertisement.jpg",
    caption: "The future is electric. Sustainable energy for everyone. #Tesla #ElectricVehicle",
    remixCount: 1823,
    likes: 4123,
    isLiked: false,
    comments: 201,
    category: "Tech",
    topComments: [
      { user: "eco_warrior", text: "This is the future!", likes: 38 },
    ],
  },

  {
    id: 6,
    brand: "Spotify",
    location: "Stockholm, Sweden",
    image: "/spotify-music-streaming-advertisement.jpg",
    caption: "Music for everyone. Discover, stream, and share the soundtrack to your life.",
    remixCount: 2134,
    likes: 4567,
    isLiked: false,
    comments: 234,
    category: "Viral",
    topComments: [
      { user: "music_lover", text: "The colors are amazing!", likes: 56 },
      { user: "dj_alex", text: "Perfect vibe", likes: 41 },
    ],
  },
]

export default function HomePage() {
  const router = useRouter()
  const [isRemixModalOpen, setIsRemixModalOpen] = useState(false)
  const [isUploadModalOpen, setIsUploadModalOpen] = useState(false)
  const [selectedAd, setSelectedAd] = useState<(typeof mockAds)[0] | null>(null)
  const [ads, setAds] = useState(mockAds)
  const [deletingAdId, setDeletingAdId] = useState<string | number | null>(null)
  const [searchQuery, setSearchQuery] = useState("")

  const filteredAds = searchQuery
    ? ads.filter(ad =>
        ad.brand.toLowerCase().includes(searchQuery.toLowerCase()) ||
        ad.caption.toLowerCase().includes(searchQuery.toLowerCase()) ||
        ad.category.toLowerCase().includes(searchQuery.toLowerCase())
      )
    : ads

  // Load ads from Supabase on page load
  useEffect(() => {
    const loadAds = async () => {
      try {
        console.log('🔄 Starting to load ads from Supabase...')
        const supabaseAds = await getAllAds()
        console.log('✅ Loaded ads from Supabase:', supabaseAds.length, 'ads')
        console.log('📦 Raw Supabase data:', supabaseAds)

        // Transform Supabase ads to match the format expected by the component
        const transformedAds = supabaseAds.map((ad: any) => {
          const imageUrl = ad.image_url || ad.video_url
          const isVideo = !ad.image_url && ad.video_url
          console.log('🔄 Transforming ad:', {
            id: ad.id,
            title: ad.title,
            imageUrl,
            videoUrl: ad.video_url,
            isVideo,
            brand: ad.companies?.name
          })

          // Get the prompts count by counting the array length
          const promptsCount = ad.prompts?.length || 0

          return {
            id: ad.id,
            brand: ad.companies?.name || 'Unknown',
            location: ad.location || ad.companies?.location || 'Unknown',
            image: imageUrl,
            caption: ad.title || '',
            remixCount: promptsCount,
            likes: ad.likes || 0,
            isLiked: false,
            comments: promptsCount,
            category: 'Tech', // You can add this to your schema later
            topComments: [],
            isUserCreated: true
          }
        })

        // Combine with mock ads (user uploaded first, then mock ads)
        setAds([...transformedAds, ...mockAds])
        console.log('✅ Total ads in feed:', transformedAds.length, 'from Supabase +', mockAds.length, 'mock =', transformedAds.length + mockAds.length)
      } catch (error) {
        console.error('❌ Error loading from Supabase:', error)
        console.warn('⚠️ Supabase unavailable, using mock data only')
        // Keep using mock ads on error - this is expected if database isn't set up
        setAds(mockAds)
      }
    }

    loadAds()
  }, [])

  const handleUpload = async (adData: { brand: string; title: string; imageUrl: string; category: string; companyId: string; location: string; isVideo?: boolean }) => {
    try {
      console.log('Upload started with data:', adData)

      // First, get or create the company
      console.log('Getting or creating company:', adData.brand)
      const company = await getOrCreateCompany(adData.brand)
      console.log('Company retrieved:', company)

      // Then save the ad with the URL from upload and get the returned data
      console.log('Saving ad to database...')

      // Check if it's a video from the upload response or file extension
      const isVideoFile = adData.isVideo || adData.imageUrl?.match(/\.(mp4|webm|mov)$/i)

      console.log('File type check:', { isVideo: isVideoFile, url: adData.imageUrl })

      const savedAd = await saveAd(
        company.id,
        adData.title,
        isVideoFile ? '' : adData.imageUrl, // Image URL (empty string if video)
        adData.location, // Location from form
        isVideoFile ? adData.imageUrl : undefined // Vi
[truncated — 14793 more characters]
```

### frontend/app/challenges/page.tsx

```typescript
"use client"

import { Card, CardContent } from "@/components/ui/card"
import { Button } from "@/components/ui/button"
import { Badge } from "@/components/ui/badge"
import { Progress } from "@/components/ui/progress"
import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"
import { Trophy, Clock, Users, DollarSign, Calendar } from "lucide-react"

const activeChallenges = [
  {
    id: 1,
    title: "Super Bowl LVIII Remix Challenge",
    brand: "Pepsi",
    image: "/pepsi-super-bowl-halftime-show-ad.jpg",
    prize: "$10,000",
    participants: 1247,
    submissions: 3456,
    endDate: "2025-03-15",
    daysLeft: 12,
    category: "Super Bowl",
    description: "Create the best remix of the iconic Super Bowl halftime show ad and compete for the grand prize",
    isEntered: true,
    myRank: 45,
  },
  {
    id: 2,
    title: "Tech Innovation Showcase",
    brand: "Apple",
    image: "/apple-iphone-product-advertisement.jpg",
    prize: "$5,000",
    participants: 892,
    submissions: 2134,
    endDate: "2025-03-20",
    daysLeft: 17,
    category: "Tech",
    description: "Submit your vision of Apple's future tech - top submission wins",
    isEntered: false,
  },
  {
    id: 3,
    title: "Sustainable Fashion Forward",
    brand: "Nike",
    image: "/nike-athletic-shoe-advertisement.jpg",
    prize: "$7,500",
    participants: 1089,
    submissions: 2891,
    endDate: "2025-03-25",
    daysLeft: 22,
    category: "Fashion",
    description: "Compete to create the most impactful sustainability message for Nike",
    isEntered: true,
    myRank: 12,
  },
  {
    id: 4,
    title: "Fast Food Frenzy",
    brand: "McDonald's",
    image: "/mcdonalds-burger-advertisement.jpg",
    prize: "$3,500",
    participants: 654,
    submissions: 1567,
    endDate: "2025-03-18",
    daysLeft: 15,
    category: "Food",
    description: "Create a mouth-watering remix that makes people crave fast food",
    isEntered: false,
  },
  {
    id: 5,
    title: "Electric Dreams",
    brand: "Tesla",
    image: "/tesla-electric-car-advertisement.jpg",
    prize: "$6,000",
    participants: 823,
    submissions: 1893,
    endDate: "2025-03-22",
    daysLeft: 19,
    category: "Tech",
    description: "Show the future of electric vehicles in your unique style",
    isEntered: false,
  },
]

const upcomingChallenges = [
  {
    id: 4,
    title: "Summer Vibes Campaign",
    brand: "Coca-Cola",
    image: "/coca-cola-super-bowl-commercial.jpg",
    prize: "$8,000",
    startDate: "2025-03-18",
    category: "Viral",
  },
  {
    id: 5,
    title: "Electric Future",
    brand: "Tesla",
    image: "/tesla-electric-car-advertisement.jpg",
    prize: "$12,000",
    startDate: "2025-03-22",
    category: "Tech",
  },
]

const pastWinners = [
  {
    id: 1,
    challenge: "Holiday Magic 2024",
    winner: "Sarah Chen",
    prize: "$10,000",
    image: "/nike-athletic-shoe-advertisement.jpg",
    votes: 8234,
  },
  {
    id: 2,
    challenge: "New Year Revolution",
    winner: "Marcus Johnson",
    prize: "$7,500",
    image: "/apple-iphone-product-advertisement.jpg",
    votes: 7891,
  },
]

export default function ChallengesPage() {
  return (
    <div className="min-h-screen pb-12">
      {/* Header */}
      <div className="border-b">
        <div className="container mx-auto px-4 h-24 flex items-center">
          <h1 className="text-3xl font-bold">Challenges</h1>
        </div>
      </div>

      {/* Content */}
      <div className="w-full pt-4">
        <Tabs defaultValue="active" className="w-full">
          <div className="border-b bg-background sticky top-16 z-40">
            <div className="container mx-auto px-4">
              <TabsList className="bg-transparent h-auto w-full justify-start rounded-none border-0 p-0">
                <TabsTrigger
                  value="active"
                  className="rounded-none border-b-2 border-transparent data-[state=active]:border-purple-600 data-[state=active]:bg-transparent data-[state=active]:text-purple-600 px-6 py-2"
                >
                  Active Challenges
                </TabsTrigger>
                <TabsTrigger
                  value="upcoming"
                  className="rounded-none border-b-2 border-transparent data-[state=active]:border-purple-600 data-[state=active]:bg-transparent data-[state=active]:text-purple-600 px-6 py-2"
                >
                  Upcoming
                </TabsTrigger>
                <TabsTrigger
                  value="winners"
                  className="rounded-none border-b-2 border-transparent data-[state=active]:border-purple-600 data-[state=active]:bg-transparent data-[state=active]:text-purple-600 px-6 py-2"
                >
                  Past Winners
                </TabsTrigger>
              </TabsList>
            </div>
          </div>

          <div className="container mx-auto px-4 mt-8">

          <TabsContent value="active" className="space-y-8">
            {/* My Challenges Section */}
            {activeChallenges.filter(c => c.isEntered).length > 0 && (
              <div>
                <div className="mb-4">
                  <h2 className="text-2xl font-bold">My Challenges</h2>
                </div>
                <div className="grid md:grid-cols-2 lg:grid-cols-3 gap-6">
                  {activeChallenges.filter(c => c.isEntered).map((challenge) => (
                    <Card key={challenge.id} className="overflow-hidden hover:shadow-xl transition-all group flex flex-col border-2 border-primary/20">
                      <div className="relative overflow-hidden">
                        <img
                          src={challenge.image || "/placeholder.svg"}
                          alt={challenge.title}
                          className="w-full h-48 object-cover group-hover:scale-105 transition-transform duration-300"
                        />
                        <div className="absolute top-3 right-3">
                     
[truncated — 11087 more characters]
```

### frontend/app/profile/page.tsx

```typescript
"use client"

import { useState } from "react"
import { Card, CardContent } from "@/components/ui/card"
import { Button } from "@/components/ui/button"
import { Badge } from "@/components/ui/badge"
import { Avatar, AvatarFallback, AvatarImage } from "@/components/ui/avatar"
import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"
import {
  Settings,
  Trophy,
  Heart,
  Sparkles,
  TrendingUp,
  Calendar,
  Award,
  Crown,
  Zap,
  Target,
  Gift,
  Bookmark,
  CreditCard,
  Coffee,
  Shirt,
  Ticket
} from "lucide-react"

const userStats = {
  username: "creative_maker",
  displayName: "Alex Rivera",
  bio: "Digital creator Making brands better, one remix at a time",
  joinDate: "January 2025",
  points: 8420,
  remixCount: 127,
  likesReceived: 5234,
  followers: 892,
  following: 156,
  creditsRemaining: 3,
}

const badges = [
  { id: 1, name: "100 Remix Master", icon: Sparkles, color: "gradient-primary", unlocked: true },
  { id: 2, name: "Viral Creator", icon: TrendingUp, color: "gradient-primary", unlocked: true },
  { id: 3, name: "Brand Champion", icon: Crown, color: "gradient-primary", unlocked: false },
  { id: 4, name: "Top 10 Creator", icon: Trophy, color: "gradient-primary", unlocked: true },
  { id: 5, name: "Lightning Fast", icon: Zap, color: "gradient-primary", unlocked: false },
  { id: 6, name: "Challenge Winner", icon: Target, color: "gradient-primary", unlocked: true },
]

const myRemixes = [
  {
    id: 1,
    brand: "Nike",
    image: "/nike-athletic-shoe-advertisement.jpg",
    prompt: "Make the shoes glow with neon colors",
    likes: 1247,
    views: 8234,
    createdAt: "2 days ago",
  },
  {
    id: 2,
    brand: "Apple",
    image: "/apple-iphone-product-advertisement.jpg",
    prompt: "Add holographic display effects",
    likes: 2891,
    views: 12453,
    createdAt: "5 days ago",
  },
  {
    id: 3,
    brand: "Coca-Cola",
    image: "/coca-cola-super-bowl-commercial.jpg",
    prompt: "Transform into retro 80s aesthetic",
    likes: 3456,
    views: 15678,
    createdAt: "1 week ago",
  },
  {
    id: 4,
    brand: "Tesla",
    image: "/tesla-electric-car-advertisement.jpg",
    prompt: "Add cyberpunk city background",
    likes: 1823,
    views: 9876,
    createdAt: "1 week ago",
  },
  {
    id: 5,
    brand: "McDonald's",
    image: "/mcdonalds-burger-advertisement.jpg",
    prompt: "Make it look like a movie poster",
    likes: 987,
    views: 5432,
    createdAt: "2 weeks ago",
  },
  {
    id: 6,
    brand: "Spotify",
    image: "/spotify-music-streaming-advertisement.jpg",
    prompt: "Add vibrant music waves",
    likes: 2134,
    views: 11234,
    createdAt: "2 weeks ago",
  },
]

const savedRemixes = [
  
  {
    id: 8,
    brand: "Amazon",
    creator: "Marcus Johnson",
    image: "/amazon-prime-delivery-advertisement.jpg",
    prompt: "Add drone delivery in cyberpunk city",
    likes: 3214,
    views: 14567,
    savedAt: "3 days ago",
  },
  {
    id: 9,
    brand: "Pepsi",
    creator: "Emma Rodriguez",
    image: "/pepsi-super-bowl-halftime-show-ad.jpg",
    prompt: "Turn into 80s music video aesthetic",
    likes: 5678,
    views: 23456,
    savedAt: "5 days ago",
  },
]

const rewards = [
  {
    id: 1,
    name: "Nike Air Max Sneakers",
    company: "Nike",
    icon: Shirt,
    milestone: "Create 50 remixes on Nike ads",
    progress: 34,
    goal: 50,
    description: "Limited edition Nike Air Max for top Nike creators",
    unlocked: false,
  },
  {
    id: 2,
    name: "iPhone 16 Pro",
    company: "Apple",
    icon: Gift,
    milestone: "Reach 10K likes on Apple ad remixes",
    progress: 8234,
    goal: 10000,
    description: "Win the latest iPhone 16 Pro",
    unlocked: false,
  },
  {
    id: 3,
    name: "$100 Starbucks Gift Card",
    company: "Starbucks",
    icon: Coffee,
    milestone: "Create viral remix (50K+ views) for Starbucks",
    progress: 23450,
    goal: 50000,
    description: "Exclusive reward for viral creators",
    unlocked: false,
  },
  {
    id: 4,
    name: "$50 Amazon Gift Card",
    company: "Amazon",
    icon: Gift,
    milestone: "Top 3 remix on Amazon challenge",
    progress: 1,
    goal: 3,
    description: "Finish in top 3 of active Amazon challenge",
    unlocked: true,
  },
  {
    id: 5,
    name: "Tesla Model Y Test Drive",
    company: "Tesla",
    icon: Ticket,
    milestone: "Win Tesla remix challenge",
    progress: 0,
    goal: 1,
    description: "Win the monthly Tesla remix challenge",
    unlocked: false,
  },
  {
    id: 6,
    name: "Coca-Cola VIP Event Pass",
    company: "Coca-Cola",
    icon: Ticket,
    milestone: "Featured in Coca-Cola's top 10 remixes",
    progress: 1,
    goal: 1,
    description: "VIP access to Coca-Cola creator summit",
    unlocked: true,
  },
]

export default function ProfilePage() {
  const [activeTab, setActiveTab] = useState("saved")

  return (
    <div className="min-h-screen pb-12">
      {/* Header Section */}
      <section className="bg-white dark:bg-slate-900 py-12 px-4 border-b">
        <div className="container mx-auto">
          <div className="flex flex-col md:flex-row items-center md:items-start gap-6">
            {/* Avatar */}
            <Avatar className="h-32 w-32 ring-4 ring-primary/30 dark:ring-primary shadow-xl">
              <AvatarImage src="" />
              <AvatarFallback className="text-4xl font-bold bg-primary text-white">AR</AvatarFallback>
            </Avatar>

            {/* User Info */}
            <div className="flex-1 text-center md:text-left">
              <div className="flex flex-col md:flex-row md:items-center gap-3 mb-3">
                <h1 className="text-3xl md:text-4xl font-bold text-foreground">{userStats.displayName}</h1>
                <Badge className="bg-primary/10 dark:bg-primary/20 text-primary dark:text-primary border-0 w-fit mx-auto md:mx-0">
                  @{userStats.username}
                </Badge>
              </div>
              <p className="text-lg text-mut
[truncated — 15521 more characters]
```

### frontend/app/api/upload/route.ts

```typescript
import { NextRequest, NextResponse } from 'next/server';
import { randomUUID } from 'crypto';
import { supabase } from '@/lib/supabase';

export async function POST(request: NextRequest) {
  try {
    const formData = await request.formData();
    const file = formData.get('file') as File;
    const brand = formData.get('brand') as string;
    const title = formData.get('title') as string;
    const location = formData.get('location') as string;
    const category = formData.get('category') as string;
    const companyId = formData.get('companyId') as string;

    if (!file || !brand || !title || !location || !category || !companyId) {
      return NextResponse.json(
        { error: 'Missing required fields' },
        { status: 400 }
      );
    }

    // Validate file type
    const isImage = file.type.startsWith('image/');
    const isVideo = file.type.startsWith('video/');
    
    if (!isImage && !isVideo) {
      return NextResponse.json(
        { error: 'Only image and video files are allowed' },
        { status: 400 }
      );
    }

    // Upload to Supabase Storage
    const fileType = isVideo ? 'video' : 'image';
    const fileExt = file.name.split('.').pop();
    const fileName = `${randomUUID()}.${fileExt}`;
    const filePath = `${fileType}s/${fileName}`;

    // Convert file to buffer
    const bytes = await file.arrayBuffer();
    const buffer = Buffer.from(bytes);

    // Upload to Supabase Storage
    console.log('Attempting to upload to Supabase storage:', { filePath, fileType });
    
    const { data: uploadData, error: uploadError } = await supabase.storage
      .from('ads')
      .upload(filePath, buffer, {
        contentType: file.type,
        cacheControl: '3600'
      });

    if (uploadError) {
      console.error('Error uploading to Supabase storage:', {
        message: uploadError.message,
        error: uploadError,
        filePath
      });
      
      // Fallback: return a placeholder URL so the ad can still be saved
      // For now, we'll save to localStorage and later upload to storage
      return NextResponse.json({
        success: true,
        filename: URL.createObjectURL(file), // Temporary object URL
        brand,
        title,
        location,
        category,
        isVideo: isVideo,
        fileType: file.type,
        storageFailed: true
      });
    }

    console.log('Upload successful:', uploadData);

    // Get public URL
    const { data: { publicUrl } } = supabase.storage
      .from('ads')
      .getPublicUrl(filePath);

    console.log('Public URL:', publicUrl);

    return NextResponse.json({
      success: true,
      filename: publicUrl,
      brand,
      title,
      location,
      category,
      isVideo: isVideo,
      fileType: file.type
    });

  } catch (error) {
    console.error('Error uploading file:', error);
    return NextResponse.json(
      { error: 'Failed to upload file' },
      { status: 500 }
    );
  }
}

```

### frontend/app/api/analyze-prompts/route.ts

```typescript
import { NextRequest, NextResponse } from 'next/server';

interface PromptAnalysis {
  themes: string[];
  emotionalTone: string;
  styleReferences: string[];
  intent: string;
}

export async function POST(request: NextRequest) {
  try {
    const { prompts } = await request.json();
    
    if (!prompts || !Array.isArray(prompts)) {
      return NextResponse.json(
        { error: 'Missing or invalid prompts array' },
        { status: 400 }
      );
    }

    const apiKey = process.env.CLAUDE_API_KEY;
    if (!apiKey) {
      console.error('Missing CLAUDE_API_KEY in environment variables');
      return NextResponse.json(
        { error: 'Claude API key not configured' },
        { status: 500 }
      );
    }

    // Prepare the system prompt and user prompts for analysis
    const systemPrompt = `You are an expert in analyzing creative ad remixes and marketing content.
    Analyze the provided ad remix prompts and extract key information.

    Return ONLY valid JSON (no markdown, no code blocks, no extra text) with this exact structure:
    {
      "themes": ["list", "of", "main", "themes"],
      "emotionalTone": "overall emotional tone",
      "styleReferences": ["list", "of", "style", "references"],
      "intent": "summarized user intent"
    }`;

    const userPrompt = `Analyze these ad remix prompts and extract themes, emotional tone, style references, and intent:\n\n${prompts.join("\n")}`;

    // Call Claude API
    const response = await fetch('https://api.anthropic.com/v1/messages', {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        'x-api-key': apiKey,
        'anthropic-version': '2023-06-01'
      },
      body: JSON.stringify({
        model: 'claude-sonnet-4-5-20250929',
        max_tokens: 1024,
        system: systemPrompt,
        messages: [
          {
            role: 'user',
            content: userPrompt
          }
        ]
      })
    });

    if (!response.ok) {
      const error = await response.text();
      console.error('Claude API error:', error);
      return NextResponse.json(
        { error: 'Failed to analyze prompts' },
        { status: 500 }
      );
    }

    const data = await response.json();
    const content = data.content[0].text;

    // Extract JSON from markdown code blocks or plain text
    const jsonMatch = content.match(/```(?:json)?\s*([\s\S]*?)\s*```/) ||
                     content.match(/\{[\s\S]*\}/);

    if (!jsonMatch) {
      console.error('No JSON found in Claude response:', content);
      return NextResponse.json(
        { error: 'Failed to parse analysis response' },
        { status: 500 }
      );
    }

    const jsonStr = jsonMatch[1] || jsonMatch[0];
    const analysis = JSON.parse(jsonStr);

    return NextResponse.json(analysis);

  } catch (error) {
    console.error('Error analyzing prompts:', error);
    return NextResponse.json(
      { error: 'Internal server error', details: error instanceof Error ? error.message : 'Unknown error' },
      { status: 500 }
    );
  }
}

```

[33 more indexed source files omitted to keep this export small. The full file list is in the Codebase structure section above.]