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VibeDoc

๐Ÿš€ Your AI Product Manager & Architect - Transform ideas into complete development plans with AI coding prompts in 60-180 seconds

Install / Use

/learn @calderbuild/VibeDoc
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

๐Ÿš€ VibeDoc: Your AI Product Manager & Architect

License: MIT Python 3.11+ Gradio PRs Welcome

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Transform Ideas into Complete Development Plans in 60-180 Seconds

AI-powered Product Manager & Software Architect that generates technical documentation, architecture diagrams, and AI coding prompts

๐ŸŒ Online Demo | ๐ŸŽฌ Demo Video | ๐Ÿค Contributing | ๐Ÿ’ฌ Discussions | ไธญๆ–‡ๆ–‡ๆกฃ

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โœจ Why VibeDoc?

As a developer, product manager, or entrepreneur, you face these challenges:

  • ๐Ÿ’ญ Great Ideas, No Plan? You have ideas but don't know how to turn them into actionable development plans
  • โฐ Documentation Takes Forever? Writing technical specs and architecture docs consumes massive time
  • ๐Ÿค– AI Tools Confusing? You want AI-assisted coding but struggle with effective prompt engineering
  • ๐Ÿ“Š Missing Professional Diagrams? You need architecture, flow, and Gantt charts but lack design tools expertise

VibeDoc Solves Everything!

VibeDoc Interface

๐ŸŽฏ Core Features

๐Ÿ“‹ Intelligent Development Plan Generation

Enter your product idea - AI generates a complete plan in 60-180 seconds:

  • Product Overview - Background, target users, core value proposition
  • Technical Solution - Tech stack selection, architecture design, technology comparison
  • Development Plan - Phased implementation, timeline, resource allocation
  • Deployment Strategy - Environment setup, CI/CD pipeline, operations monitoring
  • Growth Strategy - Market positioning, operations advice, growth tactics

๐Ÿค– AI Coding Prompt Generation

Generate ready-to-use prompts for each feature module, supporting:

  • โœ… Claude - Code generation, architecture design
  • โœ… GitHub Copilot - Intelligent code completion
  • โœ… ChatGPT - Technical consultation, code optimization
  • โœ… Cursor - AI-assisted programming

AI Coding Prompts

๐Ÿ“Š Auto-Generated Visual Diagrams

Professional diagrams using Mermaid:

  • ๐Ÿ—๏ธ System Architecture - Component relationships visualization
  • ๐Ÿ“ˆ Business Flowcharts - Business logic visualization
  • ๐Ÿ“… Gantt Charts - Project timeline at a glance
  • ๐Ÿ“Š Tech Comparison Tables - Technology decision reference

๐Ÿ“ Multi-Format Export

One-click export for different scenarios:

  • Markdown (.md) - Version control friendly, GitHub display
  • Word (.docx) - Business documents, project reports
  • PDF (.pdf) - Formal proposals, print archives
  • HTML (.html) - Web display, online sharing

Generated Example

๐Ÿ’ก Real-World Example

Input Idea

Develop an AR sign language translation app that can translate sign language
into voice and text in real-time, and also translate voice and text into
sign language gestures displayed in AR

Generated Output

๐Ÿ“„ View Complete Development Plan (10,000+ words)

The AI-generated plan includes:

1. Product Overview

  • Target users (deaf community, healthcare workers, educators)
  • Core features (real-time translation, multi-language support, AR visualization)
  • Market positioning and competitive analysis

2. Technical Architecture

Complete system architecture with Mermaid diagrams showing:

  • User interface components
  • Backend services
  • ML model integration
  • Database design
  • AR rendering pipeline

3. Technology Stack

  • Frontend: React Native (cross-platform)
  • Backend: Node.js + Express
  • ML Models: TensorFlow for sign language recognition
  • NLP: spaCy for natural language processing
  • AR: ARKit (iOS) / ARCore (Android)
  • Database: MongoDB

4. Development Timeline

6-month plan with 3 major milestones:

  • Month 1-2: Core recognition & translation engine
  • Month 3-4: AR integration & UI development
  • Month 5-6: Testing, optimization & deployment

5. 12+ AI Coding Prompts

Ready-to-use prompts for each module. Example:

Feature: Hand Gesture Recognition Model

Context:
Building a real-time hand gesture recognition system for sign language translation.
Need to detect and classify hand positions, movements, and facial expressions.

Requirements:
- Process video frames at 30+ FPS
- Recognize 500+ sign language gestures
- Support continuous gesture sequences
- Handle varying lighting conditions

Tech Stack:
- TensorFlow/Keras for model training
- MediaPipe for hand landmark detection
- OpenCV for image preprocessing

Constraints:
- Must run on mobile devices (iOS/Android)
- Model size < 50MB for mobile deployment
- Inference time < 100ms per frame

Expected Output:
- Model architecture code
- Training pipeline
- Data preprocessing functions
- Mobile optimization strategies

๐Ÿš€ Quick Start

๐ŸŒ Online Demo (Recommended)

๐Ÿ‘‰ Try VibeDoc Now - No installation required!

Experience the full functionality:

  1. Enter your product idea (e.g., "Build a smart fitness app")
  2. Optionally add reference URLs for context
  3. Click generate and wait 60-180 seconds
  4. Get complete development plan with AI coding prompts
  5. Export to Markdown/Word/PDF/HTML formats

๐Ÿ’ป Local Installation

Prerequisites

Installation Steps

# 1. Clone the repository
git clone https://github.com/JasonRobertDestiny/VibeDoc.git
cd VibeDoc

# 2. Create virtual environment (recommended)
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Configure environment variables
cp .env.example .env
# Edit .env file and add your API Key

Configuration

In .env file:

# Required: SiliconFlow API Key (free registration)
SILICONFLOW_API_KEY=your_api_key_here

# Optional: Advanced Configuration
API_TIMEOUT=300
LOG_LEVEL=INFO
ENVIRONMENT=production

Run Application

python app.py

Application starts at:

  • Local: http://localhost:7860
  • Network: http://0.0.0.0:7860

๐Ÿณ Docker Deployment (Optional)

# Build image
docker build -t vibedoc .

# Run container
docker run -p 7860:7860 \
  -e SILICONFLOW_API_KEY=your_key \
  vibedoc

๐Ÿ—๏ธ Technical Architecture

Modular architecture design:

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚         Gradio Web Interface            โ”‚
โ”‚   (User Interaction + UI + Export)      โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                  โ”‚
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ–ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚       Core Processing Engine            โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚  โ€ข Input Validation & Optimization      โ”‚
โ”‚  โ€ข AI Generation Coordination           โ”‚
โ”‚  โ€ข Content Quality Control              โ”‚
โ”‚  โ€ข Multi-format Export                  โ”‚
โ””โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
   โ”‚        โ”‚          โ”‚         โ”‚
   โ–ผ        โ–ผ          โ–ผ         โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚ AI   โ”‚ โ”‚Prompt  โ”‚ โ”‚Contentโ”‚ โ”‚Export    โ”‚
โ”‚Model โ”‚ โ”‚Optimizerโ”‚ โ”‚Validatorโ”‚ โ”‚Manager   โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

Technology Stack

  • Frontend: Gradio 5.34.1 - Fast AI app interface
  • AI Model: Qwen2.5-72B-Instruct - Alibaba Cloud
  • Chart Rendering: Mermaid.js - Code-based diagrams
  • Document Export: python-docx, reportlab
  • Async Processing: asyncio, aiofiles

๐Ÿ“Š Performance Metrics

| Metric | Performance | |--------|-------------| | Generation Speed | 60-180 seconds | | Success Rate | >95% | | Content Quality | 85/100 average | | Export Formats | 4 formats |

๐ŸŽจ Use Cases

๐Ÿ‘จโ€๐Ÿ’ป Developers

  • โœ… Validate technical feasibility quickly
  • โœ… Generate project documentation
  • โœ… Get AI coding prompts
  • โœ… Learn architecture best practices

๐Ÿ“Š Product Managers

  • โœ… Transform requirements into technical solutions
  • โœ… Create project planning documents
  • โœ… Estimate development cycles
  • โœ… Build project proposals

๐ŸŽ“ Students & Learners

  • โœ… Learn software development best practices
  • โœ… Understand architecture design
  • โœ… Prepare for technical interviews
  • โœ… Plan graduation projects

๐Ÿš€ Entrepreneurs

  • โœ… Validate product ideas quickly
  • โœ… Generate technical plans for investors
  • โœ… Plan MVP development
  • โœ… Assess implementation costs

๐Ÿค Contributing

We welcome all contributions:

  • ๐Ÿ› Report Bugs
  • ๐Ÿ’ก Suggest Features
  • ๐Ÿ“ Improve Documentation
  • ๐Ÿ”ง Submit Code

Steps

  1. Fork this project
  2. Create feature branch (git checkout -b feature/AmazingFeature)
  3. Commit changes (git commit -m 'Add AmazingFeature')
  4. Push to branch (git push origin feature/AmazingFeature)
  5. Submit Pull Request

See CONTRIBUTING.md for details.

๐Ÿ’ฌ Join Community

Join the VibeDoc community to share experiences, get support, and discuss ideas!

<div align="center"> <img src="./image/discussion_group.jpg" width="300" alt="VibeDoc Community QR Code">

Scan to Join VibeDoc Community

Share Experiences | Get Support | Join Discussions

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๐Ÿ“ Documentation

๐ŸŽฏ Roadmap

v2.1 (Planned)

  • [ ] More AI mo

Related Skills

View on GitHub
GitHub Stars372
CategoryDevelopment
Updated4d ago
Forks49

Languages

Python

Security Score

100/100

Audited on Apr 3, 2026

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