Introduce hook and context management to OpenSearch Agents

[mingshl]

Description

Add Complete Context Management Framework with Memory-Integrated Hook Events to ML Agents

This PR introduces a comprehensive context management system for ML agents, featuring memory-integrated hook
events, complete hook registry with fault-tolerant execution, enhanced context integration, and intelligent
resource management for enterprise-grade deployments.

Major Features:

1. Complete Hook Registry System
   • Fault-Tolerant Event Emission: emitEvent() with exception isolation and comprehensive logging
   • Thread-Safe Operations: ConcurrentHashMap ensuring concurrent callback registration and execution
   • Callback Management: Type-safe callback registration with monitoring capabilities
   • Production-Grade Error Handling: Individual callback failures don't affect system operation

2. Comprehensive Hook Event Architecture
   • HookEvent Base Class: Abstract base with invocation state for all lifecycle events
   • PreLLMEvent: pre llm event with context integration and retrieved re-act interactions, including tool used result/ completed steps
   • EnhancedPostToolEvent: Tool event with context integration
   • Event Hierarchy: Well-designed inheritance from HookEvent to specialized events

3. Complete CRUD REST API Implementation
   • Create Operations: MLCreateContextManagementTemplateAction, MLCreateContextManagementTemplateRequest,
   MLCreateContextManagementTemplateResponse
   • Read Operations: MLGetContextManagementTemplateAction, MLGetContextManagementTemplateRequest,
   MLGetContextManagementTemplateResponse
   • Delete Operations: MLDeleteContextManagementTemplateAction, MLDeleteContextManagementTemplateRequest,
   MLDeleteContextManagementTemplateResponse
   • Full CRUD Lifecycle: Complete template management with create, read, and delete operations

4. Context Management Integration
   • ML Agent Integration: contextManagementName and contextManagement fields with validation
   • Template System: ContextManagementTemplate with hooks, validation, and serialization
   • Hook Provider Integration: ContextManagerHookProvider registers callbacks for all event types

5. Rich Context State Management
   • ContextManagerContext: Comprehensive context with prompts, history, tools, interactions, and parameters
   • Utility Methods: getEstimatedTokenCount(), getMessageCount(), addParameter(), addToolInteraction()
   • Memory Integration: Context managers can access both current context and retrieved memory
   • Dynamic Modification: Runtime context updates with memory and invocation state tracking

6. Event-Driven Execution Pipeline
   • Tool Event Processing: handlePostTool() processes enhanced tool events with context
   • Pre-LLM Processing: handlePreLLM() processes context before LLM execution
   • Memory Event Processing: handlePostMemory() processes memory events with context and history
   • Automatic Execution: All events processed automatically through hook registry

7. Complete Activation Rules System
   • TokensExceedRule: Context-aware activation using comprehensive token estimation
   • MessageCountExceedRule: Conversation length management with memory integration
   • CompositeActivationRule: Complex conditions considering memory and context state

8. Token Counting Architecture
   • TokenCounter Interface: Standardized interface with multiple truncation strategies
   • Context Integration: Token counters integrated with activation rules and memory state
   • Pluggable Design: Interface supports model-specific implementations

9. Pluggable Context Manager Architecture
   • ContextManagerConfig: Configuration with type, activation, and manager settings
   • Template Management: Complete template system with memory-integrated hooks
   • Registry Integration: Managers registered for memory, tool, and LLM events

Technical Highlights:
• Comprehensive Event Model: Complete lifecycle coverage with memory, tool, and LLM events
• Fault-Tolerant Processing: Exception isolation ensures system stability across all event types
• Rich Context Access: Context managers have access to full context and memory

Architecture Benefits:
• Complete Lifecycle Coverage: Events cover all major phases of ML agent execution
• Integrated Memory Management: Memory retrieval and context management work together seamlessly
• Enterprise Reliability: Fault-tolerant design with comprehensive error handling

Use Cases:
• Comprehensive Resource Management: Manage tokens across current context and memory history

Impact:
• Comprehensive Agent Lifecycle: Full coverage of memory, tool, and LLM execution phases
• Advanced AI Orchestration: Sophisticated context management with memory integration

Check List

• New functionality includes testing.
• New functionality has been documented.
• API changes companion pull request created.
• Commits are signed per the DCO using --signoff.
• Public documentation issue/PR created.

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