Implement Multi-Agent System with LangGraph Supervisor Pattern and Branch Isolation

[zhangfengcdt]

Summary

This PR implements a complete solution to the "context bleeding" problem in
multi-agent systems using ProllyTree's Git-like branching with LangGraph's
supervisor pattern. The implementation demonstrates how isolated memory branches
prevent cross-contamination between specialized agents while maintaining proper
coordination and audit trails.

Key Features Implemented

🏗️ LangGraph Supervisor Architecture

• Proper delegation pattern: Supervisor intelligently routes customers to appropriate specialists
• Function-based nodes: Clean implementation using LangGraph's StateGraph with conditional routing
• State management: Dictionary-based state handling compatible with LangGraph's internal processing
• Workflow visualization: Auto-generated Mermaid diagrams showing agent interaction flow

🌿 Git-like Branch Isolation System

• BranchedMemoryService: Core service managing isolated agent workspaces
• Automatic branch creation: Each agent gets unique isolated branch (session-{id}-{agent}-{uuid})
• Metadata tracking: Complete branch genealogy with timestamps and parent relationships
• Commit history: Git-like audit trail of all agent operations and merges

🔍 Semantic Validation & Context Bleeding Prevention

• Domain validation: Prevents billing agents from making technical recommendations
• Cross-contamination detection: Validates agent outputs stay within their
  expertise domains
• Controlled merging: Safe integration of isolated agent results back to main memory
• Conflict resolution: Handles validation failures with detailed error reporting

🤖 Specialized Agent Implementations

• TroubleshootingAgent: Handles technical issues (slow internet, service outages,
  hardware problems)
• BillingAgent: Manages billing disputes, payment issues, account charges
• CustomerHistoryAgent: Analyzes customer relationships, escalation needs, priority
  handling

📊 Comprehensive Demo & Testing

• Realistic scenarios: Telecommunications customer support use cases
• Before/after analysis: Shows memory state changes and branch creation
• Performance metrics: Tracks agent coordination, validation success rates
• Integration testing: Works with run_examples.sh build system

Technical Architecture

  │                     LangGraph Supervisor Architecture                   │
  └─────────────────────────────────────────────────────────────────────────┘

  START → Supervisor → [Conditional Routing] → Agent → Validation → END
              │              │                    │         │
              │              ▼                    │         │
              │     ┌─────────────────┐          │         │
              │     │ Troubleshooting │          │         │
              │     │ Billing         │          │         │
              │     │ Customer History│          │         │
              │     └─────────────────┘          │         │
              │                                  │         │
              └─────── Branch Isolation ─────────┘         │
                             │                             │
                       ProllyTree Store                    │
                      (Git-like branches)                  │
                             │                             │
                      Semantic Validation ←────────────────┘

Benefits Demonstrated

1. Zero Context Bleeding: Agents cannot access each other's specialized data
2. Intelligent Routing: Supervisor correctly delegates based on issue classification
3. Audit Compliance: Complete Git-like history of all agent decisions
4. Semantic Safety: Validation prevents inappropriate cross-domain recommendations
5. Scalable Architecture: Easy to add new specialized agents with automatic isolation
6. Production Ready: Error handling, logging, and comprehensive test scenarios