feat(memory): integrate memory system with context engine (#97)

## Changes

### New Context Type
- Add MEMORY to ContextType enum for agent memory context
- Create MemoryContext class with subtypes (working, episodic, semantic, procedural)
- Factory methods: from_working_memory, from_episodic_memory, from_semantic_memory, from_procedural_memory

### Memory Context Source
- MemoryContextSource service fetches relevant memories for context assembly
- Configurable fetch limits per memory type
- Parallel fetching from all memory types

### Agent Lifecycle Hooks
- AgentLifecycleManager handles spawn, pause, resume, terminate events
- spawn: Initialize working memory with optional initial state
- pause: Create checkpoint of working memory
- resume: Restore from checkpoint
- terminate: Consolidate working memory to episodic memory
- LifecycleHooks for custom extension points

### Context Engine Integration
- Add memory_query parameter to assemble_context()
- Add session_id and agent_type_id for memory scoping
- Memory budget allocation (15% by default)
- set_memory_source() for runtime configuration

### Tests
- 48 new tests for MemoryContext, MemoryContextSource, and lifecycle hooks
- All 108 memory-related tests passing
- mypy and ruff checks passing

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

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

backend/app/services/context/__init__.py

@@ -114,6 +114,8 @@ from .types import (
     ContextType,
     ConversationContext,
     KnowledgeContext,
+    MemoryContext,
+    MemorySubtype,
     MessageRole,
     SystemContext,
     TaskComplexity,
@@ -149,6 +151,8 @@ __all__ = [
     "FormattingError",
     "InvalidContextError",
     "KnowledgeContext",
+    "MemoryContext",
+    "MemorySubtype",
     "MessageRole",
     "ModelAdapter",
     "OpenAIAdapter",