feat(ai): complete Phase 2/3 documentation and memory system improvements

Phase completion and enhancement updates:

## Documentation Added
- Phase 2 completion: Memory system implementation details
- Phase 3 completion: Research capabilities and tool integration
- Session documentation: Model testing, VRAM optimization analysis
- Test results: Comprehensive prompt testing (v1_verbose: 87/100)
- Tool logging implementation guide

## System Prompts
- Added prompts.py with 7 tested variants for A/B testing
- v1_verbose, v2_concise, v3_imperative, v4_minimal, etc.
- Comprehensive testing results for each variant
- Production-ready prompt selection guidance

## Memory System Enhancements
- Multi-tenancy support: Added user_id parameter throughout
- System message filtering: Don't store system messages in history
- Improved conversation turn tracking with user isolation
- Enhanced memory manager for better multi-user support

## AI Controller Improvements
- Better memory integration with user_id support
- Enhanced error handling for memory operations
- Improved token tracking for usage monitoring
- Skip system message storage (part of agent state)

## Portainer Client
- Comprehensive API client (148 lines)
- Stack management and service monitoring
- Container operations with full error handling
- Async support for all operations

## Architecture Documentation
- Updated agent flow diagrams for ADK architecture
- Enhanced core-api README with current setup
- Updated Docker compose stack configuration
- Complete testing and validation documentation

docs/architecture/agent-flow-diagrams.md

@@ -15,29 +15,31 @@ This document shows the data flow through the agent system for various scenarios
 │                    (or any OpenAI client)                        │
 └────────────────────────┬────────────────────────────────────────┘
                          │ POST /v1/chat/completions
-                         │ {"use_agent": true/false}
+                         │
                          ▼
 ┌─────────────────────────────────────────────────────────────────┐
 │                      Core API (FastAPI)                          │
 │  ┌──────────────────────────────────────────────────────────┐   │
 │  │         AI Controller (ai_controller.py)                  │   │
-│  │  • Routes to agent or direct LLM based on use_agent      │   │
+│  │  • Routes all requests to unified agent                  │   │
 │  │  • Converts OpenAI format ↔ agent format                 │   │
 │  └─────────┬────────────────────────────────────────┬───────┘   │
-│            │ use_agent=false                        │            │
-│            │                         use_agent=true │            │
-└────────────┼────────────────────────────────────────┼───────────┘
-             │                                        │
-             ▼                                        ▼
-    ┌────────────────┐                    ┌──────────────────────┐
-    │ Direct to      │                    │  Unified Agent       │
-    │ Ollama         │                    │  (orchestrator.py)   │
-    │ (any model)    │                    │  • LangGraph ReAct   │
-    └────────────────┘                    │  • mistral:7b only   │
-                                          │  • Tool calling      │
-                                          └──────────┬───────────┘
-                                                     │
-                                          ┌──────────▼───────────┐
+│            │                         │            │
+│            │                          │            │
+└────────────┼─────────────────────────────────────────────────────┘
+             │
+             ▼
+    ┌──────────────────────┐
+    │  Unified Agent       │
+    │  (orchestrator.py)   │
+    │  • LangGraph ReAct   │
+    │  • mistral:7b        │
+    │  • Tool calling      │
+    │  • Decides: tools    │
+    │    or direct answer  │
+    └──────────┬───────────┘
+               │
+    ┌──────────▼───────────┐
                                           │   Agent Tools        │
                                           │   (tools.py)         │
                                           │  • Infrastructure    │
@@ -57,13 +59,13 @@ This document shows the data flow through the agent system for various scenarios
 │ User     │  "What is Docker?"
 └────┬─────┘
      │ POST /v1/chat/completions
-     │ use_agent: true
+     │ 
      ▼
 ┌────────────────────────────────────────────┐
 │ Core API - AI Controller                   │
 │                                            │
 │ 1. Parse request                           │
-│ 2. Check use_agent flag → TRUE            │
+│ 2. Routes to unified agent                 │
 │ 3. Extract message & history               │
 └────┬───────────────────────────────────────┘
      │
@@ -142,7 +144,7 @@ This document shows the data flow through the agent system for various scenarios
 ┌──────────┐
 │ User     │  "What's the weather in SF?"
 └────┬─────┘
-     │ use_agent: true
+     │ 
      ▼
 ┌────────────────────────────────────────────┐
 │ AI Controller                              │
@@ -594,7 +596,7 @@ Multi-Tool Flow:
 | Scenario | Model Used | Reason |
 |----------|-----------|--------|
 | **Agent mode** (any query) | `mistral:7b` | Supports tool calling |
-| **Direct chat** (use_agent=false) | User's choice | gemma:2b, gemma:7b, etc. |
+| **Direct chat** () | User's choice | gemma:2b, gemma:7b, etc. |
 | **Embeddings** | `nomic-embed-text` (via Ollama) | No local PyTorch needed |
 
 ### Why mistral:7b for Agent?