Merge feature/advanced-analysis into develop - Add multi-modal search, temporal analysis, clustering, and cross-reference capabilities

# Conflicts:
#	.claude/settings.local.json
#	README.md
#	ROADMAP.md
#	app/version.py
#	dashboard_server.pid
#	docs/DASHBOARD_DEPLOYMENT.md
#	tests/integration/test_api_endpoints.py
#	tests/unit/test_core_functionality.py
#	tests/unit/test_version_system.py

Author: raold

.claude/settings.local.json

@@ -17,6 +17,18 @@
       "Bash(python -m pytest tests/ --no-cov -q --tb=no)",
       "Bash(python -m pytest tests/multimodal/test_models.py -v)",
       "Bash(python -m pytest tests/multimodal/test_models.py::TestMultiModalMemory::test_memory_validation_importance -v)",
+      "Bash(ls:*)",
+      "Bash(mkdir:*)",
+      "Bash(set PYTHONPATH=.)",
+      "Bash(set USE_MOCK_DATABASE=true)",
+      "Bash(find:*)",
+      "Bash(true)",
+      "Bash(mv:*)",
+      "Bash(git commit:*)",
+      "Bash(del \"C:\\Users\\dro\\second-brain\\verify_version_tests.py\")",
+      "Bash(set PYTHONIOENCODING=utf-8)",
+      "Bash(git push:*)",
+      "Bash(git checkout:*)",
       "Bash(dir:*)",
       "Bash(python:*)",
       "Bash(del test_multimodal_integration.py)",

CHANGELOG.md

@@ -5,7 +5,44 @@ All notable changes to Second Brain will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [2.5.0-dev] - 2025-07-19 - **PHASE 2 COMPLETE** ✅
+## [2.4.3] - 2025-07-19 - **PRODUCTION RELEASE** ✅
+
+### 🎉 Production Release: Enhanced Dashboard & Memory Architecture Foundation
+
+**Release Highlights**: Complete dashboard redesign with comprehensive version management, enhanced development status monitoring, and production-ready memory architecture foundation.
+
+#### 📊 Dashboard System Enhancement  
+- **Complete Dashboard Redesign** - New `working_dashboard.html` with improved layout and comprehensive version timeline
+- **Enhanced Version Management** - Complete roadmap from v2.4.3 through v3.0.0 (Neuromorphic Memory System)
+- **Advanced Development Status** - Real-time monitoring with detailed project component tracking
+- **Comprehensive Data Visualization** - 8-column roadmap tables with memory architecture specifications
+
+#### 🏗️ Memory Architecture Foundation
+- **Advanced Modularization Complete** - Production-ready modular system (8 components, 3,704+ lines)
+- **Enhanced Detector Implementations** - 4 advanced detection algorithms with parallel processing
+- **Production Orchestration Services** - Complete workflow management with monitoring
+- **Database Abstraction Layer** - Clean interfaces eliminating database coupling
+
+#### ✅ Version Timeline Features
+- **v2.5.0 (Testing)** - Integration Testing & Advanced Memory Features  
+- **v2.6.0 (Development)** - Multi-Modal Memory with Enhanced Cross-Platform Support
+- **v2.7.0 (Planned)** - Multi-Modal Memory System with advanced AI integration
+- **v2.8.0 (Planned)** - MemOS Foundation with memory-as-operating-system paradigm
+- **v3.0.0 (Vision)** - Neuromorphic Memory System with brain-inspired architecture
+
+#### Technical Improvements
+- Enhanced dashboard server with comprehensive API endpoints
+- Improved development status tracking with detailed feature completion metrics  
+- Advanced git branch visualization (develop → testing → main flow)
+- Enhanced project documentation and production deployment readiness
+
+#### Fixed
+- Dashboard layout and rendering issues
+- Missing version timeline data in development roadmap
+- Branch flow clarity and active development visualization
+- Data loading and display optimization
+
+## [2.5.0-dev] - 2025-07-19 - **PHASE 2 ARCHIVE** ⏳
 
 ### 🎉 Phase 2: Advanced Modularization - **100% COMPLETE**
 

README.md

@@ -6,6 +6,35 @@
 
 ## 🚀 **v2.6.0-dev Multimodal Memory System - COMPLETED**
 
+### 🎯 New Ingestion Features (from v2.5.0):
+- **Intelligent Entity Extraction** - Automatic NER with SpaCy and custom patterns for people, organizations, locations, dates, and more
+- **Advanced Topic Modeling** - LDA, keyword-based classification, and domain detection for content categorization
+- **Relationship Detection** - Discover connections between entities using dependency parsing and pattern matching
+- **Intent Recognition** - Understand user intent (questions, todos, ideas, decisions) with urgency and sentiment analysis
+- **Automatic Embeddings** - Generate vector embeddings with chunking support for semantic search
+- **Structured Data Extraction** - Extract tables, lists, key-value pairs, and code snippets from unstructured text
+- **Content Classification** - Intelligent quality assessment, domain detection, and memory type suggestions
+- **Streaming Architecture** - Real-time async processing pipeline with batching, retries, and error handling
+- **Advanced Validation** - Multi-level validation framework with business rules and detailed reporting
+- **Preprocessing Pipeline** - Content normalization, encoding fixes, and smart truncation
+
+## 🤖 **AI-Powered Insights & Pattern Discovery**
+
+### 🤖 New AI Features:
+- **AI-Powered Insights Engine** - Automatically generate personalized insights from your memory patterns
+- **Pattern Detection System** - Discover temporal, semantic, behavioral, structural, and evolutionary patterns
+- **Memory Clustering** - Intelligent grouping of related memories using K-means, DBSCAN, and hierarchical algorithms
+- **Knowledge Gap Analysis** - Identify missing areas in your knowledge base with AI-driven recommendations
+- **Learning Progress Tracking** - Monitor your knowledge growth and mastery levels across topics
+- **Interactive Insights Dashboard** - Beautiful visualization of AI discoveries and analytics
+
+### 📊 Analytics Capabilities:
+- **Usage Pattern Analysis** - Understand how you interact with your memories
+- **Memory Growth Metrics** - Track knowledge accumulation over time
+- **Access Pattern Insights** - Discover which memories are most valuable
+- **Tag Evolution Tracking** - See how your interests change over time
+- **Importance Shift Detection** - Identify changing priorities in your knowledge base
+
 ### 🎯 Major Achievement: Full Multimodal Support
 **Achievement**: Complete multimodal memory system with support for text, images, audio, video, and documents
 

ROADMAP.md

@@ -1,6 +1,6 @@
 # Second Brain - Development Roadmap 🗺️
 
-> **Current Version**: v2.6.0-dev (Development) | **Stable Release**: v2.4.3  
+> **Current Version**: v2.6.0-dev (Development) | **Stable Release**: v2.5.0
 > **Last Updated**: 2025-07-21
 
 ## 🎯 Vision & Goals
@@ -109,9 +109,27 @@
 - **Log Management**: Structured logging with appropriate levels
 - **Alerting**: Basic alerting for critical system events
 
-## 🔮 Planned Development (v2.5.0 - v3.0.0)
+## 🎆 Completed Features (v2.5.0)
 
-### **Phase 1: Enhanced Intelligence** (v2.5.0 - Q3 2025) ✅ COMPLETED
+### **v2.5.0: AI-Powered Intelligence & Sophisticated Ingestion** (✅ COMPLETED - July 21, 2025)
+
+#### **🤖 AI-Powered Insights & Pattern Discovery**
+- **AI Insights Engine**: Automatically generate personalized insights ✅
+- **Pattern Detection**: Temporal, semantic, behavioral patterns ✅
+- **Memory Clustering**: K-means, DBSCAN, hierarchical clustering ✅
+- **Knowledge Gap Analysis**: AI-driven learning recommendations ✅
+- **Learning Progress Tracking**: Topic mastery and growth metrics ✅
+- **Interactive Dashboard**: Beautiful visualization of discoveries ✅
+
+#### **🎯 Sophisticated Ingestion Engine**
+- **Entity Extraction**: NER with SpaCy + custom patterns ✅
+- **Topic Modeling**: LDA, keyword-based, domain detection ✅
+- **Relationship Detection**: Dependency parsing + patterns ✅
+- **Intent Recognition**: Questions, TODOs, ideas, decisions ✅
+- **Auto Embeddings**: Vector generation with chunking ✅
+- **Structured Data**: Tables, lists, code, key-values ✅
+- **Content Classification**: Quality assessment, domains ✅
+- **Streaming Architecture**: Async pipeline, validation ✅
 
 #### **🧠 Advanced Search & Discovery** ✅
 - ✅ **Multi-modal Search**: Full support for images, audio, video, and documents
@@ -133,11 +151,25 @@
 
 ### **Phase 2: Multimodal Memory System** (v2.6.0 - Q4 2025) ✅ COMPLETED AHEAD OF SCHEDULE
 
-#### **📈 Personal Analytics Dashboard**
-- **Knowledge Growth Metrics**: Track learning and memory accumulation
-- **Search Pattern Analysis**: Understand your thinking patterns
-- **Memory Usage Statistics**: Most accessed, most connected, trending topics
-- **Time-based Insights**: Knowledge evolution over time
+#### **📈 AI-Powered Insights & Pattern Discovery** (v2.5.1) ✅
+- **AI Insights Engine**: Automatically generate personalized insights ✅
+- **Pattern Detection**: Temporal, semantic, behavioral patterns ✅
+- **Memory Clustering**: K-means, DBSCAN, hierarchical clustering ✅
+- **Knowledge Gap Analysis**: AI-driven learning recommendations ✅
+- **Learning Progress Tracking**: Topic mastery and growth metrics ✅
+- **Interactive Dashboard**: Beautiful insights visualization ✅
+- **Time-based Insights**: Knowledge evolution over time ✅
+
+#### **🎯 Sophisticated Ingestion Engine** (v2.5.2) ✅
+- **Entity Extraction**: NER with SpaCy + custom patterns ✅
+- **Topic Modeling**: LDA, keyword-based, domain detection ✅
+- **Relationship Detection**: Dependency parsing + patterns ✅
+- **Intent Recognition**: Questions, TODOs, ideas, decisions ✅
+- **Auto Embeddings**: Vector generation with chunking ✅
+- **Structured Data**: Tables, lists, code extraction ✅
+- **Content Classification**: Quality, domain, importance ✅
+- **Streaming Architecture**: Async real-time processing ✅
+- **Advanced Validation**: Multi-level business rules ✅
 
 #### **🎯 Productivity Features**
 - **Memory Scheduling**: Spaced repetition for important memories
@@ -317,14 +349,14 @@
 | Version | Target Date | Focus Area | Key Features | Status |
 |---------|-------------|------------|--------------|--------|
 | **v2.5.0** | Oct 2025 | Advanced Search | Multi-modal search, semantic clustering, intent recognition | 📋 Planned |
-| **v2.5.1** | Nov 2025 | Memory Relationships | Auto relationship detection, knowledge graph, memory pathways | 📋 Planned |
-| **v2.5.2** | Dec 2025 | Intelligence Layer | Importance scoring, gap detection, automated tagging | 📋 Planned |
+| **v2.5.1** | Jul 2025 | AI-Powered Insights | Pattern detection, clustering, knowledge gaps, learning progress | ✅ Complete |
+| **v2.5.2** | Jul 2025 | Sophisticated Ingestion | Entity extraction, topic modeling, relationship detection, embeddings | ✅ Complete |
 
 ### **2.6.x Minor Series - Analytics & Productivity**
 
 | Version | Target Date | Focus Area | Key Features | Status |
 |---------|-------------|------------|--------------|--------|
-| **v2.6.0** | Jan 2026 | Personal Analytics | Knowledge growth metrics, search patterns, usage statistics | 📋 Planned |
+| **v2.6.0** | Jul 2025 | AI-Powered Insights | AI insights engine, pattern detection, clustering, gap analysis | ✅ Complete |
 | **v2.6.1** | Feb 2026 | Productivity Features | Memory scheduling, study sessions, goal-based organization | 📋 Planned |
 | **v2.6.2** | Mar 2026 | Advanced Queries | Natural language queries, complex filtering, saved searches | 📋 Planned |
 

app/app.py

@@ -48,6 +48,8 @@
 from app.routes import (
     session_router as new_session_router,
 )
+from app.routes.graph_routes import router as graph_router
+from app.routes.analysis_routes import router as analysis_router
 
 # Import bulk operations routes
 from app.routes.bulk_operations_routes import bulk_router
@@ -260,6 +262,13 @@ async def general_exception_handler(request: Request, exc: Exception):
 app.include_router(importance_router)
 app.include_router(relationship_router)
 app.include_router(bulk_router)
+app.include_router(graph_router)
+app.include_router(analysis_router)
+
+# Include insights router
+from app.routes.insights import router as insights_router
+
+app.include_router(insights_router)
 
 # Include bulk operations routes
 app.include_router(get_bulk_routes(), dependencies=[Depends(verify_api_key)])
@@ -338,6 +347,29 @@ async def mobile_interface():
         )
 
 
+# AI Insights Dashboard
+@app.get("/insights", response_class=HTMLResponse)
+async def insights_dashboard():
+    """Serve the AI insights dashboard"""
+    try:
+        with open("static/insights-dashboard.html", encoding="utf-8") as f:
+            return HTMLResponse(content=f.read())
+    except FileNotFoundError:
+        return HTMLResponse(
+            content="""
+        <html>
+        <head>
+            <title>AI Insights - Second Brain</title>
+        </head>
+        <body>
+        <h1>🧠 AI Insights Dashboard</h1>
+        <p>Insights dashboard is not available. Please check your installation.</p>
+        </body>
+        </html>
+        """
+        )
+
+
 # Health check
 @app.get(
     "/health",

app/bulk_memory_operations.py

@@ -227,7 +227,7 @@ async def _setup_tracking_tables(self):
                         status VARCHAR(20) NOT NULL,
                         error_message TEXT,
                         processed_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
-                        
+
                         INDEX (operation_id),
                         INDEX (operation_id, batch_number),
                         INDEX (memory_id)
@@ -242,7 +242,7 @@ async def _setup_tracking_tables(self):
                         metric_name VARCHAR(50) NOT NULL,
                         metric_value DECIMAL(12,4) NOT NULL,
                         recorded_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
-                        
+
                         INDEX (operation_id),
                         INDEX (metric_name),
                         INDEX (recorded_at)
@@ -534,7 +534,7 @@ async def _insert_batch(self, batch: list[BulkMemoryItem], conn: asyncpg.Connect
                 content, memory_type, embedding, importance_score,
                 semantic_metadata, episodic_metadata, procedural_metadata, metadata
             )
-            SELECT * FROM UNNEST($1::text[], $2::memory_type_enum[], $3::vector[], 
+            SELECT * FROM UNNEST($1::text[], $2::memory_type_enum[], $3::vector[],
                                  $4::decimal[], $5::jsonb[], $6::jsonb[], $7::jsonb[], $8::jsonb[])
             RETURNING id
         """,
@@ -555,7 +555,7 @@ async def _store_operation_result(self, result: BulkOperationResult):
                 async with self.database.pool.acquire() as conn:
                     await conn.execute(
                         """
-                        UPDATE bulk_operations 
+                        UPDATE bulk_operations
                         SET result = $1, completed_at = NOW(), updated_at = NOW()
                         WHERE operation_id = $2
                     """,

app/bulk_memory_operations_advanced.py

@@ -561,7 +561,7 @@ async def _process_update_batches(self, memories, update_op, progress, config, c
                     params.append(ids)
 
                     query = f"""
-                        UPDATE memories 
+                        UPDATE memories
                         SET {update_clause}, updated_at = NOW()
                         WHERE id = ANY(${len(params)}::uuid[])
                         RETURNING id
@@ -614,7 +614,7 @@ async def _process_delete_batches(self, memories, progress, config, conn, error_
                 ids = [str(record["id"]) for record in batch]
 
                 query = """
-                    DELETE FROM memories 
+                    DELETE FROM memories
                     WHERE id = ANY($1::uuid[])
                     RETURNING id
                 """

app/conversation_processor.py

@@ -376,12 +376,12 @@ def setup_conversation_monitoring():
     # - Email parsing
     # - Chat application hooks
 
-    print("🎯 Conversation monitoring setup complete")
-    print("📝 Dashboard will auto-update when CTO discusses:")
-    print("   • New features and capabilities")
-    print("   • Architectural challenges")
-    print("   • Project priorities and timelines")
-    print("   • Technical improvements")
+    print("Conversation monitoring setup complete")
+    print("Dashboard will auto-update when CTO discusses:")
+    print("   - New features and capabilities")
+    print("   - Architectural challenges")
+    print("   - Project priorities and timelines")
+    print("   - Technical improvements")
 
     return processor
 

app/dashboard.py

@@ -148,7 +148,7 @@ def __init__(self, project_name: str = "Project Pipeline"):
 
     def initialize_project_pipeline(self):
         """Initialize Project Pipeline with baseline milestones and structure"""
-        print("🚀 Initializing Project Pipeline Dashboard...")
+        print("Initializing Project Pipeline Dashboard...")
 
         # Phase 1: Pipeline Foundation
         milestone_1 = Milestone(
@@ -340,7 +340,7 @@ def add_new_feature_context(self, feature_name: str, description: str, priority:
         Automatically add new feature/goal based on conversation context
         This method is called when CTO discusses new architectural features
         """
-        print(f"🎯 Adding new feature context: {feature_name}")
+        print(f"Adding new feature context: {feature_name}")
 
         # Create new milestone for the feature
         feature_milestone = Milestone(
@@ -735,7 +735,7 @@ def load_dashboard_data(self):
                 self.adrs = {k: ArchitecturalDecision(**v) for k, v in data["adrs"].items()}
 
         except Exception as e:
-            print(f"⚠️ Error loading dashboard data: {e}")
+            print(f"Warning: Error loading dashboard data: {e}")
 
     def generate_visual_report(self) -> str:
         """Generate visual dashboard report for CTO overview"""