cognee

gmakstutis/cognee

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Author	SHA1	Message	Date
vasilije	73b293ed71	feat: enhance frontend graph visualization with cluster boundaries and improved rendering - Add cluster boundary visualization with color-coded type grouping - Implement new MemoryGraphVisualization component for Cognee integration - Add TypeScript types for Cognee API integration (CogneeAPI, NodeSet) - Enhance node swarm materials with better color hierarchy - Improve edge materials with opacity controls - Add metaball density rendering for visual clustering - Update demo and dataset visualization pages with new features 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>	2026-01-12 07:24:32 +01:00
vasilije	63a50e6709	feat: create isolated graph visualization demo with enhanced aesthetics Add standalone visualization demo page with rich AI/ML knowledge graph: New Demo Page (/visualize/demo): - 52 interconnected nodes covering AI, ML, DL, NLP, CV, and RL concepts - 56 semantic relationships showing concept hierarchies and connections - Interactive legend with node type categorization - Real-time statistics panel - Beautiful UI with instructions overlay - Toggleable legend and stats panels Visual Enhancements: - Expanded color palette from 5 to 10 vibrant, distinguishable colors - Darker background (#0a0a0f) for better contrast - Improved force layout parameters for better node distribution - Enhanced zoom range (0.5x - 6x) for better exploration - Smoother damping (0.08) for fluid camera motion - Increased label limit (15) for better context at high zoom Performance Optimizations: - 800 initial layout iterations for stable starting position - Optimized spring coefficients for balanced clustering - Maintained scalability with existing rendering architecture The mock dataset represents a comprehensive AI/ML knowledge graph with: - Core concepts (AI, ML, DL, NLP, CV, RL) - Algorithms (SVM, K-Means, Q-Learning, etc.) - Architectures (CNN, RNN, Transformer, GAN, etc.) - Technologies (BERT, GPT, ResNet, YOLO, etc.) - Applications (Chatbots, Autonomous Vehicles, Medical Imaging, etc.) - Data and optimization components All improvements maintain the metaball rendering and scalability of the original Three.js implementation. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>	2026-01-11 17:08:18 +01:00
Boris Arzentar	77a4b914e1	fix: integrate new grapg visualization	2025-10-27 01:13:54 +01:00

Author

SHA1

Message

Date

vasilije

73b293ed71

feat: enhance frontend graph visualization with cluster boundaries and improved rendering

- Add cluster boundary visualization with color-coded type grouping
- Implement new MemoryGraphVisualization component for Cognee integration
- Add TypeScript types for Cognee API integration (CogneeAPI, NodeSet)
- Enhance node swarm materials with better color hierarchy
- Improve edge materials with opacity controls
- Add metaball density rendering for visual clustering
- Update demo and dataset visualization pages with new features

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

2026-01-12 07:24:32 +01:00

vasilije

63a50e6709

feat: create isolated graph visualization demo with enhanced aesthetics

Add standalone visualization demo page with rich AI/ML knowledge graph:

**New Demo Page** (/visualize/demo):
- 52 interconnected nodes covering AI, ML, DL, NLP, CV, and RL concepts
- 56 semantic relationships showing concept hierarchies and connections
- Interactive legend with node type categorization
- Real-time statistics panel
- Beautiful UI with instructions overlay
- Toggleable legend and stats panels

**Visual Enhancements**:
- Expanded color palette from 5 to 10 vibrant, distinguishable colors
- Darker background (#0a0a0f) for better contrast
- Improved force layout parameters for better node distribution
- Enhanced zoom range (0.5x - 6x) for better exploration
- Smoother damping (0.08) for fluid camera motion
- Increased label limit (15) for better context at high zoom

**Performance Optimizations**:
- 800 initial layout iterations for stable starting position
- Optimized spring coefficients for balanced clustering
- Maintained scalability with existing rendering architecture

The mock dataset represents a comprehensive AI/ML knowledge graph with:
- Core concepts (AI, ML, DL, NLP, CV, RL)
- Algorithms (SVM, K-Means, Q-Learning, etc.)
- Architectures (CNN, RNN, Transformer, GAN, etc.)
- Technologies (BERT, GPT, ResNet, YOLO, etc.)
- Applications (Chatbots, Autonomous Vehicles, Medical Imaging, etc.)
- Data and optimization components

All improvements maintain the metaball rendering and scalability
of the original Three.js implementation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

2026-01-11 17:08:18 +01:00

Boris Arzentar

77a4b914e1

fix: integrate new grapg visualization

2025-10-27 01:13:54 +01:00

3 commits