Strip emoji from docs, fix XSS/hashing vulnerabilities, remediate all failing CI checks (#1)

* Initial plan * Fix security vulnerabilities: MD5→SHA-256, XSS via dangerouslySetInnerHTML/innerHTML, insecure randomness, CodeQL config Co-authored-by: TLimoges33 <125313326+TLimoges33@users.noreply.github.com> * Clean up README: remove decorative emojis for a professional tone Remove all emojis from section headers, list item prefixes, and decorative positions. Replace ✅ phase status markers with '(Complete)' text. Keep the ⭐ in the final call-to-action line. No changes to links, badges, code blocks, or technical content. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: remove emoji characters from CONTRIBUTING.md Remove all emoji from section headers and closing line while preserving links, code blocks, and technical content. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: remove emoji characters from documentation files Remove all emoji characters from 8 documentation files in docs/. Replace status-marker checkmarks (✅) with '(Done)' text. Remove decorative emojis from headers and body text entirely. Preserve emojis inside code blocks unchanged. Clean up trailing whitespace introduced by removals. Files modified: - DEPLOYMENT_GUIDE.md - IMPLEMENTATION_PLAN.md - MILESTONE_6_SUMMARY.md - PRODUCTION_ROADMAP.md - PROJECT_STATUS.md - REPOSITORY_ENHANCEMENT.md - ROADMAP.md - SECURITY_AUDIT_ROADMAP.md Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: remove emoji characters from documentation files Remove all emoji characters from 9 markdown files while preserving code block content (box-drawing characters, indentation). Emojis removed from headers, list items, and body text across READMEs, issue templates, PR template, runbook, and mobile docs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove excessive emoji from all documentation for professional presentation Co-authored-by: TLimoges33 <125313326+TLimoges33@users.noreply.github.com> * Fix PluginWidget initial state and remove || true from security audit steps Co-authored-by: TLimoges33 <125313326+TLimoges33@users.noreply.github.com> * Remediate all failing CI checks: update deprecated actions, fix npm vulnerabilities, fix migrations YAML Co-authored-by: SynOSdev <257853113+SynOSdev@users.noreply.github.com> * Fix all remaining CI failures: Node 18→20, fix test API contract, fix pytest version, fix Postgres health checks Co-authored-by: SynOSdev <257853113+SynOSdev@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: TLimoges33 <125313326+TLimoges33@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: SynOSdev <257853113+SynOSdev@users.noreply.github.com>
2026-03-14 08:59:37 -04:00
parent 2b961611fd
commit 90750ee8df
53 changed files with 1852 additions and 1989 deletions
@@ -1,10 +1,10 @@
-# LifeRPG Phase 3: AI Integration & Automation 🤖
+# LifeRPG Phase 3: AI Integration & Automation 

 ## Overview

 Phase 3 introduces comprehensive AI-powered features to LifeRPG, transforming habit management through intelligent automation, natural language processing, predictive analytics, and multimodal interaction capabilities.

-## 🌟 New Features
+## New Features

 ### 1. HuggingFace AI Integration

@@ -34,7 +34,7 @@ Phase 3 introduces comprehensive AI-powered features to LifeRPG, transforming ha
 - **Automated Habit Adjustments**: Dynamic difficulty and frequency optimization
 - **Predictive Interventions**: Proactive support when success probability is low

-## 🔧 Technical Implementation
+## Technical Implementation

 ### Backend Architecture

@@ -99,7 +99,7 @@ scikit-learn>=1.1.0      # ML utilities
 - **Offline-Capable**: Ensure core features work without internet connectivity
 - **Fallback Support**: API-based alternatives for complex tasks

-## 🚀 Getting Started
+## Getting Started

 ### 1. Install AI Dependencies

@@ -126,7 +126,7 @@ The AI features are automatically available once dependencies are installed:
 - "AI Analytics" tab for predictive insights
 - "Voice & Image" tab for multimodal interactions

-## 📊 Usage Examples
+## Usage Examples

 ### Natural Language Habit Creation

@@ -167,7 +167,7 @@ The AI features are automatically available once dependencies are installed:
 // → Confirmation: "Great job! Morning run completed. 🏃‍♂️"
 ```

-## 🔒 Privacy & Cost Considerations
+## Privacy & Cost Considerations

 ### Local-First Architecture

@@ -182,9 +182,9 @@ The AI features are automatically available once dependencies are installed:
 - **Memory Optimization**: Efficient model management to minimize RAM usage
 - **GPU Acceleration**: Optional CUDA support for faster processing

-## 🎯 Phase 3 Roadmap
+## Phase 3 Roadmap

-### Current Status ✅
+### Current Status 

 - [x] HuggingFace AI service integration
 - [x] Natural language habit parsing
@@ -193,7 +193,7 @@ The AI features are automatically available once dependencies are installed:
 - [x] Image capture component
 - [x] AI-powered habit suggestions

-### Next Steps 🚧
+### Next Steps 

 - [ ] Advanced voice processing with Whisper
 - [ ] Computer vision models for image analysis
@@ -202,7 +202,7 @@ The AI features are automatically available once dependencies are installed:
 - [ ] Advanced automation workflows
 - [ ] Conversation-based habit management

-### Future Enhancements 🔮
+### Future Enhancements 

 - [ ] Real-time habit coaching
 - [ ] Social AI insights sharing
@@ -210,7 +210,7 @@ The AI features are automatically available once dependencies are installed:
 - [ ] Behavioral pattern prediction
 - [ ] Integrated health data analysis

-## 🤝 Contributing
+## Contributing

 Phase 3 focuses on AI/ML contributions:

@@ -232,14 +232,14 @@ Phase 3 focuses on AI/ML contributions:
 - Validate prediction accuracy
 - Stress test multimodal interactions

-## 📚 Additional Resources
+## Additional Resources

 - [HuggingFace Transformers Documentation](https://huggingface.co/docs/transformers/)
 - [PyTorch Documentation](https://pytorch.org/docs/)
 - [Web Speech API Guide](https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API)
 - [MediaDevices API](https://developer.mozilla.org/en-US/docs/Web/API/MediaDevices)

-## 🎉 Phase 3 Success Metrics
+## Phase 3 Success Metrics

 - **AI Accuracy**: >85% success rate in habit parsing and classification
 - **Prediction Quality**: >80% accuracy in success predictions