YAP. — AI Portfolio Content Engine

Transform raw code repositories into enterprise-grade READMEs and high-converting executive social proof in seconds.

💡 Why This Exists

Top 1% engineers often suffer from mediocre personal positioning. Writing high-impact READMEs and technical posts takes valuable focus away from shipping code. YAP! bridges this gap by directly ingesting GitHub repositories, extracting core architectural context, and generating production-ready documentation and LinkedIn content tuned to distinct tone profiles.

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⚡ Key Features

• Dual-Path Repo Streamer: Blazing-fast tarball memory extraction with a multi-threaded (ThreadPoolExecutor) REST API fallback for private/public GitHub repositories.
• Context-Aware Payload Trimming: Smart filtering pipeline that strips heavy dependencies (node_modules, lockfiles, binaries) to maximize LLM context efficiency under 30,000 characters.
• Resilient AI Pipeline: Built on top of the modern google-genai SDK with auto-retry mechanisms for transient 503/UNAVAILABLE service errors.
• Multi-Vibe Content Engine: Tailor social positioning using distinct engines: Corporate Alpha, Tech Influencer, and Humblebrag.
• Neo-Brutalist UX: High-contrast, zero-latency SPA state machine built for rapid workflow execution.
• Cloud-Native Architecture: Pre-configured Docker container optimized for single-worker/multi-thread deployment on Google Cloud Run or Vercel.

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🛠️ Tech Stack

• Backend: Python 3.12, Flask 3.1, Gunicorn
• LLM Engine: Google Gemini AI API (google-genai SDK)
• Data Ingestion: GitHub REST API v3, Tarball Gzip Streaming
• Frontend: HTML5, Neo-Brutalist CSS Engine, Vanilla JS State Machine
• Deployment: Docker, Google Cloud Run, Vercel Serverless

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🚀 Quick Start

Local Setup

1. Clone the repository:

   git clone https://github.com/your-username/yap.git
   cd yap

2. Configure Environment Variables: Create a .env file in the root directory:

   GEMINI_API_KEY=your_gemini_api_key_here
   GITHUB_TOKEN=your_github_pat_here # Optional, increases rate limits
   PORT=8080

3. Install Dependencies & Run:

   python3 -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt
   python app.py

   Navigate to http://localhost:8080 in your browser.

Docker Deployment

docker build -t yap-app .
docker run -p 8080:8080 -e GEMINI_API_KEY=your_key_here yap-app