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GitHub Repository Setup Information

Use this information when setting up the RAPTOR repository on GitHub.

Repository Configuration

Basic Information

Repository Name: RAPTOR

Short Description (max 350 characters):

AI-powered Content Insight Engine transforming passive media into intelligent knowledge. 85% reduction in manual tagging, 10x faster discovery through semantic search. Multi-modal analysis (video/audio/image/text), LLM-powered insights. Open source, production-ready, Kubernetes-native. Apache 2.0 | DHT Taiwan

Website: https://dhtsolution.com/

Topics/Tags

Add these topics to help discovery:

ai
artificial-intelligence
machine-learning
content-management
digital-asset-management
semantic-search
vector-database
llm
large-language-models
computer-vision
nlp
natural-language-processing
multimedia-processing
video-analysis
audio-transcription
metadata-generation
knowledge-graph
python
kubernetes
apache2
open-source
content-intelligence
media-analysis
dam
cms

About Section

Website: https://dhtsolution.com/

Topics: (Use the tags above - select most relevant 10-15)

  • ai
  • artificial-intelligence
  • machine-learning
  • content-management
  • semantic-search
  • vector-database
  • llm
  • computer-vision
  • nlp
  • kubernetes
  • python
  • digital-asset-management
  • metadata-generation

Social Preview Image

Create a 1200x630px image with:

  • RAPTOR logo
  • Tagline: "AI-Powered Content Insight Engine"
  • Key stats: "85% faster tagging | 10x better discovery"
  • DHT Solutions branding
  • Tech icons: AI, Video, Audio, Image, Text

Repository Description (Long)

# RAPTOR - AI-Powered Content Insight Engine

Transform passive media storage into an intelligent knowledge platform.

## What is RAPTOR?

RAPTOR (Rapid AI-Powered Text and Object Recognition) is a Content Insight Engine 
that revolutionizes digital asset management through AI-native architecture, 
multi-modal understanding, and semantic intelligence.

## Key Benefits

- **85% reduction** in manual content tagging
- **10x faster** content discovery
- **60% improvement** in content reuse efficiency
- Real-time insights from video, audio, images, and documents

## Core Capabilities

✨ Multi-modal content analysis (video, audio, image, text)
🔍 Semantic search with context understanding
🤖 LLM-powered metadata generation
🎯 Entity recognition and extraction
📊 Actionable insights and analytics
☸️  Production-ready, Kubernetes-native
🔒 Enterprise-grade security

## Quick Start

```bash
pip install raptor-ai
raptor serve

Developed by DHT Taiwan Team | Apache 2.0 License


### GitHub Features to Enable

- ✅ Issues
- ✅ Discussions (with categories: Announcements, Q&A, Ideas, Show and Tell, General)
- ✅ Projects (optional)
- ❌ Wiki (use docs/ folder instead)
- ✅ Sponsorships (optional)

### Branch Protection Rules

**Branch**: `main`

Enable:
- ✅ Require a pull request before merging
  - ✅ Require approvals: 1
  - ✅ Dismiss stale pull request approvals when new commits are pushed
- ✅ Require status checks to pass before merging
  - ✅ Require branches to be up to date before merging
  - Status checks: CI/CD Pipeline
- ✅ Require conversation resolution before merging
- ✅ Require signed commits (optional, for higher security)
- ✅ Include administrators
- ✅ Restrict who can push to matching branches (maintainers only)

### Labels to Create

**Type Labels**:
- `type: bug` (red) - Something isn't working
- `type: feature` (green) - New feature or request
- `type: enhancement` (blue) - Improvement to existing feature
- `type: documentation` (light blue) - Documentation improvements
- `type: question` (purple) - Further information requested

**Priority Labels**:
- `priority: critical` (dark red) - Critical priority
- `priority: high` (orange) - High priority
- `priority: medium` (yellow) - Medium priority
- `priority: low` (light gray) - Low priority

**Status Labels**:
- `status: needs-triage` (gray) - Needs review and prioritization
- `status: in-progress` (yellow) - Work in progress
- `status: blocked` (red) - Blocked by external dependency
- `status: ready-for-review` (green) - Ready for review

**Component Labels**:
- `component: core` - Core framework
- `component: api` - API and endpoints
- `component: ui` - User interface
- `component: docs` - Documentation
- `component: ci-cd` - CI/CD pipeline
- `component: video` - Video processing
- `component: audio` - Audio processing
- `component: image` - Image processing
- `component: text` - Text processing
- `component: search` - Search functionality
- `component: llm` - LLM integration

**Good First Issue**:
- `good first issue` (green) - Good for newcomers

**Help Wanted**:
- `help wanted` (purple) - Extra attention needed

### Milestones to Create

1. **Aigle 0.1.0-beta** (Current)
   - Due date: Release date
   - Description: First community beta release

2. **Aigle 0.1.1**
   - Description: Bug fixes and minor improvements

3. **Aigle 0.2.0**
   - Description: Performance improvements and new features

### GitHub Actions Secrets

Add these secrets for CI/CD (if needed):

- `PYPI_API_TOKEN` - For publishing to PyPI
- `DOCKER_USERNAME` - For Docker Hub
- `DOCKER_PASSWORD` - For Docker Hub
- `CODECOV_TOKEN` - For code coverage reporting

### Release Template

When creating releases, use this template:

```markdown
## RAPTOR Aigle 0.1.0-beta 🎉

First open-source beta release of the RAPTOR Content Insight Engine!

### 🎯 Highlights

- Multi-modal content processing (video, audio, image, text)
- Semantic search with vector embeddings
- AI-powered metadata generation
- LLM orchestration framework
- Production-ready architecture

### 📦 Installation

```bash
git clone https://github.com/DHT-AI-Studio/RAPTOR.git
cd RAPTOR/Aigle/0.1
pip install -r requirements.txt
pip install -e .

📚 Documentation

🐛 Known Issues

See CHANGELOG.md for known limitations.

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

📝 License

Apache 2.0 - See LICENSE file

Developed by DHT Taiwan Team | DHT Solutions


### Discussion Categories

Create these categories in GitHub Discussions:

1. **📢 Announcements** (Announcement type)
   - Project updates and releases
   
2. **💡 Ideas & Feature Requests**
   - Suggest new features and improvements
   
3. **🙋 Q&A** (Q&A type)
   - Ask questions about RAPTOR
   
4. **🎉 Show and Tell**
   - Share your projects using RAPTOR
   
5. **💬 General**
   - General discussion about RAPTOR

### Security

1. Enable **Security Advisories**
2. Enable **Dependabot alerts**
3. Enable **Dependabot security updates**
4. Add security policy (already in SECURITY.md)

### Insights Settings

Enable these insights:
- Pulse
- Contributors
- Community
- Traffic
- Commits
- Code frequency
- Dependency graph
- Network

---

## Social Media Setup

### Twitter/X Bio

🚀 RAPTOR - AI-Powered Content Insight Engine Transform media into intelligence 85% ⬇️ tagging | 10x ⬆️ discovery Open source | Apache 2.0 By @DHT_Taiwan 🔗 github.com/DHT-AI-Studio/RAPTOR


### LinkedIn Description

RAPTOR (Rapid AI-Powered Text and Object Recognition) is an open-source Content Insight Engine that transforms passive media storage into an intelligent knowledge platform.

Leveraging cutting-edge AI including LLMs, vector search, and multi-modal analysis, RAPTOR delivers: • 85% reduction in manual content tagging • 10x faster content discovery • Real-time insights from video, audio, images, and documents

Built for enterprise scale with Kubernetes-native architecture.

Developed by DHT Taiwan Team | Apache 2.0 License Visit: github.com/DHT-AI-Studio/RAPTOR


### Instagram Bio

🤖 AI-Powered Content Insight Engine 📹 Video | 🎵 Audio | 🖼️ Image | 📄 Text 🔍 Semantic Search | 🏷️ Auto-Tagging ⚡ 10x Faster Discovery 🌐 Open Source | Apache 2.0 👉 github.com/DHT-AI-Studio/RAPTOR


---

This information should be used when setting up the RAPTOR repository on GitHub 
and associated social media accounts.