05d39fdda8
Track A (Infrastructure & Data Layer): - docker-compose.yml with all 7 services (nginx, frontend, api, mcp, renderer, worker, postgres, redis) - docker-compose.override.yml for local dev (hot reload, port exposure) - PostgreSQL init.sql with full schema (15 tables, pgvector indexes, creator economy stubs) - .env.example with all required environment variables Track A+B (API Layer): - FastAPI app with 10 routers (auth, shaders, feed, votes, generate, desires, users, payments, mcp_keys, health) - SQLAlchemy ORM models for all 15 tables - Pydantic schemas for all request/response types - JWT auth middleware (access + refresh tokens, Redis blocklist) - Redis rate limiting middleware - Celery worker config with job stubs (render, embed, generate, feed cache, expire bounties) - Alembic migration framework Service stubs: - MCP server (health endpoint, 501 for all tools) - Renderer service (Express + Puppeteer scaffold, 501 for /render) - Frontend (package.json with React/Vite/Three.js/TanStack/Tailwind deps) - Nginx reverse proxy config (/, /api, /mcp, /renders) Project: - DECISIONS.md with 11 recorded architectural decisions - README.md with architecture overview - Sample shader seed data (plasma, fractal noise, raymarched sphere)
79 lines
2.3 KiB
Markdown
79 lines
2.3 KiB
Markdown
# 🔥 Fractafrag
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**A self-hosted GLSL shader platform — browse, create, generate, and share real-time GPU visuals.**
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Fractafrag fuses three experiences:
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- **TikTok-style adaptive feed** of living, animated shaders that learns your taste
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- **Shadertoy-style code editor** for writing, forking, and publishing GLSL shaders
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- **AI generation layer** where you describe what you want and the platform writes the shader
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Plus a **desire queue / bounty board** where users express what they want to see, and human creators or AI agents fulfill those requests.
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## Quick Start
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```bash
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# 1. Clone and configure
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cp .env.example .env
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# Edit .env with your secrets
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# 2. Launch everything
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docker compose up -d
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# 3. Open
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open http://localhost
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```
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## Architecture
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```
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nginx (reverse proxy)
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├── / → React frontend (Vite)
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├── /api/* → FastAPI backend
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└── /mcp/* → MCP server (AI agent interface)
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postgres (pgvector/pgvector:pg16) — primary datastore + vector similarity
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redis (redis:7-alpine) — cache, rate limiting, job queue
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renderer — headless Chromium shader renderer
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worker — Celery job processor (render, embed, AI generate)
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```
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## Tech Stack
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| Layer | Tech |
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|-------|------|
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| Frontend | React 18, Vite, Three.js, TanStack Query, Zustand, Tailwind CSS |
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| Backend | Python, FastAPI, SQLAlchemy, Pydantic |
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| Database | PostgreSQL 16 + pgvector, Redis 7 |
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| Jobs | Celery + Redis |
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| Renderer | Node.js + Puppeteer (Headless Chromium) |
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| MCP | Python MCP SDK, HTTP+SSE transport |
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| Payments | Stripe (subscriptions + Connect) |
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| Container | Docker Compose, single-stack |
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## Milestone Roadmap
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| Milestone | Focus | Status |
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|-----------|-------|--------|
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| **M0** | Infrastructure + Auth | 🚧 In Progress |
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| **M1** | Core Shader Loop (editor, submit, feed) | ⏳ |
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| **M2** | Intelligence Layer (MCP, recommendations) | ⏳ |
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| **M3** | Desire Economy (bounties, fulfillment) | ⏳ |
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| **M4** | Monetization (Stripe, subscriptions) | ⏳ |
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| **M5** | AI Generation (prompt → shader) | ⏳ |
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## Development
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```bash
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# API direct access (dev mode)
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http://localhost:8000/api/docs # Swagger UI
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http://localhost:8000/health # Health check
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# Services
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http://localhost:5173 # Vite dev server
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http://localhost:3200 # MCP server
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http://localhost:3100 # Renderer
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```
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## License
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Private — see DECISIONS.md for project governance.
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