Visualization Dashboard

Visualization Dashboard

Interactive web-based dashboard for exploring SuperLocalMemory v2.2.0 visually - Timeline views, semantic search explorer, knowledge graph visualization, and real-time analytics.

Keywords: visualization dashboard, web UI, timeline view, search explorer, graph visualization, memory analytics, interactive dashboard

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🎥 Dashboard Tour

Watch the full dashboard walkthrough (2 minutes):

https://superlocalmemory.com/assets/videos/dashboard-tour.mp4

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🎨 Overview

The Visualization Dashboard (new in v2.2.0) provides an interactive web interface for exploring your memories, discovering patterns, and visualizing relationships. Built with Dash/Plotly for professional-grade interactive visualizations.

Why Use the Dashboard?

Challenge	Dashboard Solution
"I have 1,000+ memories"	Timeline view shows all memories chronologically
"Can't visualize relationships"	Interactive graph shows clusters and connections
"Search is text-only"	Visual search explorer with score bars
"Want to see trends"	Analytics dashboard with charts and insights
"Need to explore clusters"	Click clusters to see all related memories

Key Features

1. 📈 Timeline View - Chronological visualization with importance indicators
2. 🔍 Search Explorer - Real-time semantic search with visual scoring
3. 🕸️ Graph Visualization - Interactive knowledge graph with zoom/pan
4. 📊 Statistics Dashboard - Memory trends, tag clouds, pattern insights
5. 🎯 Advanced Filters - Filter by tags, importance, date range, clusters
6. 🌓 Dark Mode - Easy on the eyes for long sessions
7. 📱 Responsive - Works on desktop, tablet, mobile

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🚀 Getting Started

Prerequisites

# Install optional dependencies (if not already installed)
pip install dash plotly pandas networkx

# Or install all at once
pip install -r requirements-dashboard.txt

Launch Dashboard

# Start the dashboard server
python ~/.claude-memory/ui_server.py

# Dashboard opens at: http://localhost:8765

Expected output:

╔══════════════════════════════════════════════════════════════╗
║  SuperLocalMemory v2.2.0 - Visualization Dashboard           ║
╚══════════════════════════════════════════════════════════════╝

✓ Database loaded: 523 memories
✓ Knowledge graph loaded: 8 clusters, 312 entities
✓ Pattern data loaded: 24 learned patterns

🌐 Dashboard running at: http://localhost:8765
🔧 Press Ctrl+C to stop server

[2026-02-07 14:30:00] Dash app starting...

Configuration

Custom port:

python ~/.claude-memory/ui_server.py --port 8080

Specific profile:

python ~/.claude-memory/ui_server.py --profile work

Debug mode:

python ~/.claude-memory/ui_server.py --debug

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📈 Timeline View

Visualize all your memories chronologically with importance indicators, clusters, and quick actions.

Features

Feature	Description
Chronological display	All memories sorted by date
Importance markers	Color-coded by importance (1-10)
Cluster badges	Shows which cluster each memory belongs to
Hover tooltips	Full content preview on hover
Click to expand	View full memory details
Date range filter	Filter by custom date ranges
Zoom controls	Focus on specific time periods

Color Coding

Importance levels:

• 🔴 Critical (9-10) - Red markers
• 🟠 High (7-8) - Orange markers
• 🟡 Medium (4-6) - Yellow markers
• 🟢 Low (1-3) - Green markers

Use Cases

1. Review recent work:

Select: "Last 7 days"
See: All memories from this week
Action: Quick context refresh

2. Analyze project history:

Select: Custom range (Jan 1 - Feb 7)
See: All project memories
Action: Generate project summary

3. Find forgotten decisions:

Scroll: Timeline to 3 months ago
See: Old architectural decisions
Action: Recall reasoning

Screenshots

Timeline View - Full:

Full timeline showing all memories with importance color coding and chronological organization

Timeline View - Filtered:

Filtered to last 30 days, showing cluster-organized memories

Memory Cards - Detail View:

Expanded memory cards showing content, tags, clusters, and importance scores

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🔍 Search Explorer

Real-time semantic search with visual score indicators, multiple search strategies, and instant results.

Features

Feature	Description
Live search	Results update as you type
Hybrid search	Semantic + FTS5 + Graph combined
Score visualization	Visual bars showing relevance (0-100%)
Search strategy toggle	Switch between semantic/exact/graph/hybrid
Result highlighting	Matched keywords highlighted
Cluster context	Shows related cluster for each result
Export results	Download search results as JSON/CSV

Search Strategies

1. Semantic Search (TF-IDF)

Query: "authentication patterns"
Matches: JWT implementation, OAuth flow, session management
How: Finds conceptually similar content
Speed: ~45ms

2. Full-Text Search (FTS5)

Query: "PostgreSQL 15"
Matches: Exact phrase "PostgreSQL 15"
How: Literal text matching
Speed: ~30ms

3. Graph-Enhanced Search

Query: "security"
Matches: All memories in "Auth & Security" cluster
How: Knowledge graph traversal
Speed: ~60ms

4. Hybrid Search (Default)

Query: "API design"
Matches: Best results from all three strategies
How: Combines and ranks all methods
Speed: ~80ms

Visual Score Indicators

Score bars show relevance:

• 90-100% - Perfect match (green)
• 70-89% - High relevance (yellow)
• 50-69% - Medium relevance (orange)
• Below 50% - Low relevance (red)

Advanced Search Options

Filters available:

• Minimum score threshold (slider: 0-100%)
• Date range (calendar picker)
• Tags (multi-select dropdown)
• Importance level (1-10 slider)
• Clusters (multi-select)
• Projects (dropdown)

Use Cases

1. Find related concepts:

Search: "authentication"
Strategy: Semantic
Results: JWT, OAuth, sessions, tokens, CSRF

2. Exact phrase lookup:

Search: "expires after 24 hours"
Strategy: FTS5
Results: Exact matches only

3. Explore cluster:

Search: "React"
Strategy: Graph
Results: All React-related via cluster

Screenshots

Search Explorer - Live Search:

Real-time search as you type with instant results and hybrid scoring

Search Results - Score Visualization:

Visual score bars showing relevance percentages with color-coded importance

Advanced Filters:

Advanced filter panel showing date range, tags, importance, and cluster filters

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🕸️ Graph Visualization

Interactive knowledge graph showing clusters, entities, and relationships with zoom, pan, and click-to-explore.

Features

Feature	Description
Interactive graph	Zoom, pan, drag nodes
Cluster coloring	Each cluster has unique color
Edge weights	Thicker edges = stronger relationships
Node sizing	Larger nodes = more connections
Click to focus	Click cluster to see members
Hover details	Node/edge info on hover
Layout algorithms	Force-directed, circular, hierarchical
Export graph	Save as PNG/SVG

Graph Elements

Nodes:

• Clusters - Large colored circles
• Entities - Smaller circles connected to clusters
• Memories - Smallest circles (linked to entities)

Edges:

• Cluster relationships - Dotted lines
• Entity connections - Solid lines
• Memory links - Thin lines

Colors:

• Each cluster automatically assigned unique color
• Related clusters have similar color shades
• Isolated nodes shown in gray

Layout Options

1. Force-Directed (Default)

Best for: General exploration
Behavior: Related nodes attract, unrelated repel
Use case: Discovering hidden relationships

2. Circular

Best for: Cluster comparison
Behavior: Nodes arranged in circle
Use case: Seeing all clusters equally

3. Hierarchical

Best for: Parent-child relationships
Behavior: Tree-like structure
Use case: Understanding memory organization

Interaction

Click cluster node:

• Highlights all connected memories
• Shows cluster name and member count
• Displays cluster statistics

Click entity node:

• Shows all memories containing entity
• Highlights related clusters
• Displays entity frequency

Click memory node:

• Opens memory detail card
• Shows all connected entities
• Highlights cluster membership

Drag nodes:

• Rearrange graph layout
• Fix node position
• Explore dense areas

Use Cases

1. Discover relationships:

Action: Zoom out to see full graph
Observation: "JWT" cluster connected to "API Security"
Insight: These topics are related

2. Explore cluster:

Action: Click "Authentication" cluster
View: All 12 memories in cluster
Insight: Common authentication patterns

3. Find entity usage:

Action: Click "FastAPI" entity node
View: 8 memories using FastAPI
Insight: Framework preference confirmed

Screenshots

Interactive Graph Visualization:

Interactive graph with zoom, pan, and click-to-explore functionality

Knowledge Graph - Cluster View:

Full knowledge graph showing clusters, entities, and relationships with color coding

Cluster Details:

Detailed cluster view showing all members and connections

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📊 Statistics Dashboard

Real-time analytics showing memory trends, tag clouds, pattern insights, and usage statistics.

Features

Feature	Description
Memory trends	Memories added over time (line chart)
Tag cloud	Most used tags (word cloud)
Importance distribution	Pie chart of importance levels
Cluster sizes	Bar chart of cluster member counts
Pattern confidence	Top learned patterns with scores
Access heatmap	Most accessed memories
Search trends	Most common search queries
Growth metrics	Total memories, growth rate

Widgets

1. Memory Trends (Line Chart)

Shows: Memories added per day/week/month
Options: Toggle date range (7d, 30d, 90d, all)
Insight: When you're most productive

2. Tag Cloud (Word Cloud)

Shows: Most frequent tags (size = frequency)
Options: Color schemes, min frequency
Insight: Your main topics

3. Importance Distribution (Pie Chart)

Shows: Breakdown of importance levels 1-10
Options: Show percentages, counts
Insight: How you prioritize information

4. Cluster Sizes (Bar Chart)

Shows: Number of memories per cluster
Options: Sort by size/name, show top N
Insight: Largest knowledge areas

5. Pattern Confidence (Table)

Shows: Learned patterns with confidence scores
Options: Filter by confidence threshold
Insight: Your coding identity

6. Access Heatmap (Calendar Heatmap)

Shows: Memory access frequency over time
Options: Color schemes, date ranges
Insight: Which memories you reference most

Use Cases

1. Track productivity:

Widget: Memory Trends
Period: Last 30 days
Insight: "I add more memories on Mondays"

2. Identify focus areas:

Widget: Tag Cloud
View: All tags
Insight: "authentication, react, performance are my main topics"

3. Analyze patterns:

Widget: Pattern Confidence
Threshold: 60%
Insight: "I prefer React (73%), Jest (65%), REST (81%)"

Screenshots

Statistics Dashboard - Overview:

Full statistics dashboard with memory counts, cluster distribution, and key metrics

Pattern Learning Analytics:

Learned patterns with confidence scores showing coding preferences and identity profiles

Live Events & Agent Activity:

Real-time event stream showing memory operations and agent connections

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🎯 Advanced Filters

Powerful filtering system for precise memory exploration across all dashboard views.

Filter Types

1. Date Range Filter

Options:
- Last 7 days
- Last 30 days
- Last 90 days
- Last year
- Custom range (date picker)

Use case: "Show only recent memories"

2. Tag Filter

Options:
- Multi-select dropdown
- Search within tags
- "Any of" or "All of" logic

Use case: "Show memories tagged 'authentication' AND 'security'"

3. Importance Filter

Options:
- Slider (1-10)
- Range selection (e.g., 7-10 for high priority)
- Exact value

Use case: "Show only critical memories (9-10)"

4. Cluster Filter

Options:
- Multi-select from available clusters
- Include/exclude specific clusters
- Unclustered only

Use case: "Show only 'Authentication' and 'API Design' clusters"

5. Project Filter

Options:
- Dropdown of all projects
- Multiple project selection
- Default project only

Use case: "Show memories from 'myapp' project"

6. Score Filter (Search only)

Options:
- Minimum score threshold (0-100%)
- Only perfect matches (90%+)
- Show all results

Use case: "Show only high-confidence matches (70%+)"

Filter Combinations

Example 1: Recent Critical Work

Filters:
- Date: Last 7 days
- Importance: 7-10
- Tags: work, deployment

Result: Critical work memories from this week

Example 2: Authentication Review

Filters:
- Cluster: Authentication & Security
- Date: Last 90 days
- Score: 60%+

Result: Recent auth-related memories with high relevance

Example 3: React Project Context

Filters:
- Tags: react, components
- Project: frontend-app
- Importance: 5-10

Result: Important React memories for specific project

Filter Persistence

Filters are saved across sessions:

• Dashboard remembers last used filters
• Per-view filter preferences
• Export/import filter presets

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🌓 Dark Mode

Eye-friendly dark theme for long dashboard sessions.

Features

• Toggle switch in top-right corner
• Automatic OS theme detection (optional)
• High contrast colors for readability
• Optimized for extended use
• Preference saved across sessions

Color Schemes

Light Mode:

• Background: White (#FFFFFF)
• Text: Dark gray (#333333)
• Accent: Blue (#1890FF)

Dark Mode:

• Background: Dark blue (#1E1E1E)
• Text: Light gray (#E0E0E0)
• Accent: Cyan (#00BCD4)

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🛠️ Configuration

Dashboard Settings

File: ~/.claude-memory/dashboard_config.json

{
  "port": 8000,
  "host": "127.0.0.1",
  "theme": "auto",
  "default_view": "timeline",
  "timeline": {
    "items_per_page": 50,
    "date_format": "YYYY-MM-DD HH:mm"
  },
  "search": {
    "default_strategy": "hybrid",
    "min_score": 0.5,
    "max_results": 100
  },
  "graph": {
    "layout": "force",
    "node_size_range": [10, 50],
    "edge_thickness_range": [1, 5]
  },
  "stats": {
    "refresh_interval": 60,
    "cache_enabled": true
  }
}

Customization Options

Change port:

"port": 8080

Default view:

"default_view": "search"  // Options: timeline, search, graph, stats

Search strategy:

"default_strategy": "semantic"  // Options: semantic, fts, graph, hybrid

Graph layout:

"layout": "circular"  // Options: force, circular, hierarchical

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🚀 Performance Tips

For Large Datasets (1,000+ memories)

1. Enable caching:

"stats": {
  "cache_enabled": true,
  "cache_ttl": 300  // 5 minutes
}

2. Limit timeline items:

"timeline": {
  "items_per_page": 25  // Smaller pages load faster
}

3. Use date range filters:

Instead of: Loading all 5,000 memories
Use: Filter to last 30 days (500 memories)
Result: 5x faster load time

4. Simplify graph visualization:

"graph": {
  "max_nodes": 100,  // Limit visible nodes
  "min_edge_weight": 0.5  // Hide weak connections
}

Expected Performance

Dataset Size	Timeline Load	Search Time	Graph Render
100 memories	< 100ms	35ms	< 200ms
500 memories	< 300ms	45ms	< 500ms
1,000 memories	< 500ms	55ms	< 1s
5,000 memories	< 2s	85ms	< 3s

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📱 Mobile Support

Dashboard is responsive and works on mobile devices.

Mobile Features

• Touch gestures for graph zoom/pan
• Swipe navigation between views
• Optimized layouts for small screens
• Reduced animation for performance

Mobile Limitations

• Graph visualization simplified (fewer nodes)
• Some advanced filters hidden behind menu
• Statistics widgets stacked vertically

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🔧 Troubleshooting

Dashboard won't start

Error: ModuleNotFoundError: No module named 'dash'

Solution:

pip install dash plotly pandas networkx

Port already in use

Error: OSError: [Errno 48] Address already in use

Solution:

# Use different port
python ~/.claude-memory/ui_server.py --port 8051

# Or kill existing process
lsof -ti:8765 | xargs kill

Slow graph rendering

Issue: Graph takes > 5 seconds to load

Solution:

# 1. Reduce max nodes in config
"max_nodes": 100

# 2. Use simpler layout
"layout": "circular"

# 3. Rebuild graph with higher similarity threshold
python ~/.claude-memory/graph_engine.py build --min-similarity 0.5

Memory data not showing

Issue: Dashboard shows "0 memories"

Solution:

# 1. Check database
sqlite3 ~/.claude-memory/memory.db "SELECT COUNT(*) FROM memories;"

# 2. Check profile
python ~/.claude-memory/ui_server.py --profile default

# 3. Reinitialize database (if needed)
slm status

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🎓 Tips & Tricks

1. Quick Context Refresh

Use case: Starting a new session, need context

Steps:

1. Open timeline view
2. Filter: Last 7 days
3. Scan memories chronologically
4. Export as text for AI assistant

2. Discover Hidden Patterns

Use case: Want to understand your knowledge base

Steps:

1. Open graph visualization
2. Look for dense cluster areas
3. Click clusters to explore
4. Note surprising connections

3. Track Project Progress

Use case: Review project evolution

Steps:

1. Open statistics dashboard
2. View memory trends (last 90 days)
3. Filter by project tag
4. Analyze growth and focus areas

4. Find Forgotten Decisions

Use case: "We decided something about auth..."

Steps:

1. Open search explorer
2. Search: "authentication decision"
3. Strategy: Hybrid
4. Sort by date
5. Find the decision from 2 months ago

5. Prepare for Standup

Use case: What did I work on this week?

Steps:

1. Timeline view
2. Filter: Last 7 days
3. Filter: Importance 5+
4. Export list
5. Use in standup meeting

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📸 Screenshots Gallery

Dashboard Views

Overview Dashboard (Light Mode):

Overview Dashboard (Dark Mode):

Memory Timeline:

Filtered Memories:

Memory Cards (Light Mode):

Memory Cards (Dark Mode):

Knowledge Graph

Graph Visualization:

Cluster Analysis:

Analytics & Patterns

Pattern Learning:

Live Events & Agents

Live Events (Light Mode):

Live Events (Dark Mode):

Agent Connections:

Annotated Guides

Overview - Annotated:

Memory Cards - Annotated:

Graph Visualization - Annotated:

Live Events - Annotated:

Agents Tab - Annotated:

Interactive Demos

Dashboard Tab Navigation:

Real-time Search:

Graph Interaction:

Event Stream:

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🚦 Keyboard Shortcuts

Shortcut	Action
Ctrl+1	Timeline view
Ctrl+2	Search explorer
Ctrl+3	Graph visualization
Ctrl+4	Statistics dashboard
Ctrl+F	Focus search box
Ctrl+D	Toggle dark mode
Ctrl+R	Refresh current view
Esc	Close modal/overlay

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🔗 Integration with CLI

Dashboard and CLI share the same database - changes are reflected instantly.

Real-Time Updates

Add memory via CLI:

slm remember "New memory" --tags dashboard
# Refresh dashboard → Memory appears immediately

Search via CLI, visualize in dashboard:

# 1. Search via CLI
slm recall "authentication"

# 2. Open same search in dashboard
# 3. See visual scores and graph context

Export from Dashboard, Use in CLI

Dashboard export:

• Export search results as JSON
• Use JSON in custom scripts
• Feed to other tools

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🎯 Use Cases

For Developers

1. Daily Context Refresh

View: Timeline (last 7 days)
Goal: Remember what you worked on
Time: 2 minutes

2. Architecture Review

View: Graph visualization
Goal: Understand system relationships
Time: 5 minutes

3. Pattern Analysis

View: Statistics dashboard
Goal: Learn your preferences
Time: 3 minutes

For Teams

1. Knowledge Sharing

View: Timeline (filtered by project)
Export: PDF/HTML
Share: With team members

2. Onboarding New Members

View: Graph visualization
Goal: Show project structure
Export: Screenshot

3. Sprint Planning

View: Search explorer
Query: "last sprint decisions"
Export: Decision list

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🔮 Future Enhancements

Planned for future releases:

• ✅ Real-time collaborative viewing
• ✅ Custom dashboard layouts
• ✅ Advanced analytics (NLP insights)
• ✅ Export to various formats (PDF, Markdown, HTML)
• ✅ AI-powered memory suggestions
• ✅ Integration with external tools (Notion, Obsidian)
• ✅ Mobile native app (iOS/Android)
• ✅ 3D graph visualization
• ✅ Voice search and navigation

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📚 Related Documentation

• Universal-Architecture - Learn about the architecture
• Installation - Setup guide including dashboard dependencies
• Quick-Start-Tutorial - Get started quickly
• Knowledge-Graph-Guide - Understand clustering
• CLI-Cheatsheet - Command line reference

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💡 Summary

The Visualization Dashboard transforms SuperLocalMemory from a command-line tool into a comprehensive visual knowledge management system. With timeline views, semantic search explorer, interactive graph visualization, and real-time analytics, you can:

• ✅ Explore memories visually instead of text-only search
• ✅ Discover hidden relationships via interactive graphs
• ✅ Track trends and patterns with real-time statistics
• ✅ Filter precisely with advanced multi-dimensional filters
• ✅ Work efficiently with keyboard shortcuts and dark mode

Launch in seconds:

python ~/.claude-memory/ui_server.py
# http://localhost:8765

100% local. 100% private. 100% visual.

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← Back to Home

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Created by Varun Pratap Bhardwaj Solution Architect • SuperLocalMemory

GitHub • Report Issue • Wiki