feat(ai): complete ADK migration and optimize system health checks

Major architectural changes and improvements:

## ADK Framework Migration (v0.10.0)
- Migrated from LangChain/LangGraph to Google ADK 1.3.0 with LiteLLM 1.80.5
- Improved tool calling reliability with local Ollama models
- Converted all 10 tools to ADK async generator format
- Updated streaming pipeline for ADK event system
- Enhanced error handling and agent initialization

## Model Optimization
- Switched from gemma3:12b (10GB VRAM) to gemma3:4b (4.8GB VRAM)
- Reduced VRAM usage from 91% to 43% (5.4GB freed)
- Optimized for production stability with memory headroom

## Health Check System Overhaul
- Optimized /health/full: 6ms response (was 30s+)
- Added model verification: confirms configured model is available
- New /health/diagnostics endpoint with optional deep testing
- Added currently loaded models tracking
- Clear emoji status indicators (✅/❌/⚠️)
- Fixed AGENT_AVAILABLE flag export for proper health reporting

## Ollama Client Enhancements
- Added list_models() method for model inventory
- Enhanced model verification in health checks
- Better error handling and reporting

## Documentation Updates
- Updated STATUS.md to v0.10.0-adk-migration
- Comprehensive CHANGELOG.md entry with migration details
- Updated PLANS.md showing Phase 4 complete
- Updated ai-orchestrator-plan.md with ADK status
- Added MIGRATION_PLAN_LANGCHAIN_TO_ADK.md
- Added ADK_Ollama_Research.md with implementation analysis

## Technical Details
- 10 tools: 7 infrastructure + 2 research + 1 response tool
- Framework: Google ADK with UnifiedAgent pattern
- System prompt: v7_adk_best_practice
- Container health: Now passing Docker healthchecks
- Response times: Simple queries ~0.3-1s, Research ~4-7s

services/core-api/src/config.py

@@ -51,16 +51,21 @@ class Settings(BaseSettings):
     ollama_timeout: int = 300  # 5 minutes
 
     # Model Configuration
-    # default_model: str = "phi3:mini"
-    # agent_model: str = "gemma3-tools:1b"  # Must support tool calling
-    # lightweight_models: str = "gemma3-tools:1b,phi3:mini"
-    # heavy_models: str = "mistral:7b,gemma2:9b,mixtral:8x7b"
-    # code_models: str = "codestral:latest,codegemma:latest"
-    default_model: str = "mistral:7b"
-    agent_model: str = "mistral:7b"  # Must support tool calling
-    lightweight_models: str = "gemma:2b,gemma:7b"
-    heavy_models: str = "mistral:7b,gemma2:9b,mixtral:8x7b"
+    default_model: str = "gemma3:4b"
+    agent_model: str = "gemma3:4b"  # Must support tool calling with ADK (~4GB VRAM)
+    lightweight_models: str = "gemma3-tools:1b,phi3:mini"
+    heavy_models: str = "mistral:7b,gemma2:9b,gemma3:12b,mixtral:8x7b"
     code_models: str = "codestral:latest,codegemma:latest"
+    # Previous config (gemma3:12b used ~10GB VRAM)
+    # default_model: str = "gemma3:12b"
+    # agent_model: str = "gemma3:12b"
+
+    # System Prompt Variant (for A/B testing)
+    # Options: v1_verbose, v2_concise, v3_imperative, v4_minimal, v4_gemini_suggestion, v5_adk_optimized
+    system_prompt_variant: str = "v7_adk_best_practice"
+
+    # Agent Configuration
+    agent_fallback_enabled: bool = True
 
     # Model Aliases (OpenAI → Local)
     alias_gpt35: str = "gemma:7b"