feat: Activate all dormant cognitive subsystems

backend/godelos_integration.py

@@ -12,6 +12,13 @@
 
 logger = logging.getLogger(__name__)
 
+# Attempt to import the cognitive pipeline; gracefully degrade if unavailable.
+try:
+    from godelOS.cognitive_pipeline import CognitivePipeline
+    _PIPELINE_AVAILABLE = True
+except Exception:  # noqa: BLE001
+    _PIPELINE_AVAILABLE = False
+
 class GödelOSIntegration:
     """
     A simplified working integration class for GödelOS API.
@@ -21,6 +28,7 @@ def __init__(self):
         self.initialized = False
         self.start_time = time.time()
         self.error_count = 0
+        self.cognitive_pipeline: Optional["CognitivePipeline"] = None
 
         # Enhanced knowledge store for better search
         self.simple_knowledge_store = {
@@ -71,6 +79,23 @@ async def initialize(self, pipeline_service=None, mgmt_service=None):
             self.pipeline_service = pipeline_service
             self.mgmt_service = mgmt_service
 
+            # Activate all cognitive subsystems via the unified pipeline
+            if _PIPELINE_AVAILABLE:
+                try:
+                    self.cognitive_pipeline = CognitivePipeline()
+                    self.cognitive_pipeline.initialize()
+                    logger.info(
+                        "✅ Cognitive pipeline activated — %d subsystems online",
+                        sum(
+                            1
+                            for s in self.cognitive_pipeline.get_subsystem_status().values()
+                            if s["status"] == "active"
+                        ),
+                    )
+                except Exception as exc:  # noqa: BLE001
+                    logger.warning("⚠️ Cognitive pipeline activation failed: %s", exc)
+                    self.cognitive_pipeline = None
+
             await asyncio.sleep(0.1)  # Brief pause to simulate initialization
 
             self.initialized = True
@@ -489,7 +514,7 @@ def _enhanced_search_simple_store(self, query: str) -> Optional[Dict]:
     async def get_health_status(self) -> Dict[str, Any]:
         """Get detailed health status."""
         is_healthy = self.initialized and self.error_count < 10
-        return {
+        result = {
             "healthy": is_healthy,
             "status": "healthy" if is_healthy else "unhealthy",
             "timestamp": time.time(),
@@ -501,6 +526,23 @@ async def get_health_status(self) -> Dict[str, Any]:
                 "management_service": hasattr(self, 'mgmt_service') and self.mgmt_service is not None
             }
         }
+        # Include cognitive subsystem status when the pipeline is available
+        if self.cognitive_pipeline is not None:
+            result["cognitive_subsystems"] = self.cognitive_pipeline.get_subsystem_status()
+        return result
+
+    async def get_cognitive_subsystem_status(self) -> Dict[str, Any]:
+        """Return per-subsystem activation status from the cognitive pipeline."""
+        if self.cognitive_pipeline is None:
+            return {"available": False, "subsystems": {}}
+        subsystems = self.cognitive_pipeline.get_subsystem_status()
+        active = sum(1 for s in subsystems.values() if s["status"] == "active")
+        return {
+            "available": True,
+            "active_count": active,
+            "total_count": len(subsystems),
+            "subsystems": subsystems,
+        }
 
     async def get_knowledge(
         self,

backend/unified_server.py

@@ -2325,7 +2325,7 @@ async def llm_chat_capabilities():
 async def system_status():
     """System status endpoint."""
     try:
-        return {
+        result = {
             "system": "GödelOS",
             "status": "operational",
             "version": "2.0.0",
@@ -2338,10 +2338,31 @@ async def system_status():
             },
             "timestamp": datetime.now().isoformat()
         }
+        # Include cognitive subsystem status when available
+        if godelos_integration and godelos_integration.cognitive_pipeline:
+            subsystem_status = godelos_integration.cognitive_pipeline.get_subsystem_status()
+            active = sum(1 for s in subsystem_status.values() if s["status"] == "active")
+            result["cognitive_subsystems"] = {
+                "active_count": active,
+                "total_count": len(subsystem_status),
+                "subsystems": subsystem_status,
+            }
+        return result
     except Exception as e:
         logger.error(f"Error getting system status: {e}")
         raise HTTPException(status_code=500, detail=f"Status error: {str(e)}")
 
+@app.get("/api/system/subsystems")
+async def cognitive_subsystem_status():
+    """Return per-subsystem activation status from the cognitive pipeline."""
+    try:
+        if godelos_integration:
+            return await godelos_integration.get_cognitive_subsystem_status()
+        return {"available": False, "subsystems": {}}
+    except Exception as e:
+        logger.error(f"Error getting subsystem status: {e}")
+        raise HTTPException(status_code=500, detail=f"Subsystem status error: {str(e)}")
+
 @app.get("/api/tools/available")
 async def get_available_tools():
     """Get available tools."""

docs/SUBSYSTEM_ACTIVATION_STATUS.md

@@ -0,0 +1,111 @@
+# Cognitive Subsystem Activation Status
+
+This document records which GödelOS cognitive subsystems have been wired into
+the active pipeline and which remain genuinely unimplemented or intentionally
+offline.
+
+Generated for **v0.4 – Dormant Module Activation** (issue #100).
+
+---
+
+## Active Subsystems (23 / 23 initialise successfully)
+
+| # | Subsystem | Module path | Status | Notes |
+|---|-----------|-------------|--------|-------|
+| 1 | TypeSystemManager | `godelOS/core_kr/type_system/manager.py` | **Active** | Foundational – required by almost everything |
+| 2 | KnowledgeStoreInterface | `godelOS/core_kr/knowledge_store/interface.py` | **Active** | In-memory backend with TRUTHS / BELIEFS / HYPOTHETICAL contexts |
+| 3 | UnificationEngine | `godelOS/core_kr/unification_engine/engine.py` | **Active** | Used by resolution prover and CLP module |
+| 4 | FormalLogicParser | `godelOS/core_kr/formal_logic_parser/parser.py` | **Active** | Parses logic expressions into AST |
+| 5 | ResolutionProver | `godelOS/inference_engine/resolution_prover.py` | **Active** | FOL / propositional resolution |
+| 6 | **ModalTableauProver** | `godelOS/inference_engine/modal_tableau_prover.py` | **Active** | Was dormant – now registered with InferenceCoordinator |
+| 7 | **CLPModule** | `godelOS/inference_engine/clp_module.py` | **Active** | Was dormant – constraint logic programming |
+| 8 | AnalogicalReasoningEngine | `godelOS/inference_engine/analogical_reasoning_engine.py` | **Active** | Analogy-based inference |
+| 9 | InferenceCoordinator | `godelOS/inference_engine/coordinator.py` | **Active** | Routes goals to the right prover; all 4 provers registered |
+| 10 | CachingSystem | `godelOS/scalability/caching.py` | **Active** | Memoisation / caching layer |
+| 11 | NLUPipeline | `godelOS/nlu_nlg/nlu/pipeline.py` | **Active** | Text → AST (lexical analysis, semantic interpretation, formalisation) |
+| 12 | NLGPipeline | `godelOS/nlu_nlg/nlg/pipeline.py` | **Active** | AST → Text (content planning, sentence generation, surface realisation) |
+| 13 | **SimulatedEnvironment** | `godelOS/symbol_grounding/simulated_environment.py` | **Active** | Was dormant – internal world model |
+| 14 | **PerceptualCategorizer** | `godelOS/symbol_grounding/perceptual_categorizer.py` | **Active** | Was dormant – raw percepts → symbolic vocabulary |
+| 15 | **SymbolGroundingAssociator** | `godelOS/symbol_grounding/symbol_grounding_associator.py` | **Active** | Was dormant – syntax-to-semantics bridge |
+| 16 | ActionExecutor | `godelOS/symbol_grounding/action_executor.py` | **Active** | Executes actions in the simulated environment |
+| 17 | InternalStateMonitor | `godelOS/symbol_grounding/internal_state_monitor.py` | **Active** | Introspects module state for metacognition |
+| 18 | ContextEngine | `godelOS/common_sense/context_engine.py` | **Active** | Creates / retrieves / merges named contexts |
+| 19 | **CommonSenseContextManager** | `godelOS/common_sense/manager.py` | **Active** | Was dormant – default reasoning, external KB, contextualised retrieval |
+| 20 | **MetacognitionManager** | `godelOS/metacognition/manager.py` | **Active** | Monitor → Diagnose → Plan → Modify cycle |
+| 21 | **ILPEngine** | `godelOS/learning_system/ilp_engine.py` | **Active** | Was dormant – inductive logic programming |
+| 22 | **ExplanationBasedLearner** | `godelOS/learning_system/explanation_based_learner.py` | **Active** | Was dormant – generalises from proof objects |
+| 23 | **MetaControlRLModule** | `godelOS/learning_system/meta_control_rl_module.py` | **Active** | Was dormant – RL for meta-level control decisions |
+
+**Bold** entries are the 8 subsystems that were previously dormant (implemented
+but disconnected) and are now wired into the pipeline.
+
+## Pipeline Data Flow
+
+```
+Text Input
+    │
+    ▼
+NLUPipeline  ──────────────────────────┐
+    │  (lexical analysis → semantic     │
+    │   interpretation → formalisation) │
+    ▼                                   │
+KnowledgeStoreInterface  ◄─────────────┘
+    │  (store / retrieve assertions)
+    ▼
+InferenceCoordinator
+    ├─ ResolutionProver
+    ├─ ModalTableauProver  ← dormant, now active
+    ├─ CLPModule           ← dormant, now active
+    └─ AnalogicalReasoningEngine
+    │
+    ▼
+ContextEngine + CommonSenseContextManager
+    │  (context enrichment, default reasoning)
+    ▼
+NLGPipeline  ─────► Text Output
+    (content planning → sentence generation → surface realisation)
+```
+
+Side channels fed during processing:
+
+- **SymbolGroundingAssociator** grounds abstract symbols
+- **PerceptualCategorizer** categorises raw inputs into symbols
+- **SimulatedEnvironment** supports counterfactual reasoning
+- **MetacognitionManager** monitors / diagnoses / improves processing
+- **ILPEngine** induces general rules from examples
+- **ExplanationBasedLearner** generalises from successful proofs
+- **MetaControlRLModule** learns optimal strategy selection
+
+## Genuinely Unimplemented Modules
+
+The following items are **not** source-code-complete and therefore cannot
+be activated:
+
+| Module | Notes |
+|--------|-------|
+| `godelOS/perception/` (directory) | Referenced in the issue but does not exist as a separate package. Perception is handled by `symbol_grounding/perceptual_categorizer.py`. |
+| `godelOS/environment/` (directory) | Referenced in the issue but does not exist as a separate package. Simulated environment lives in `symbol_grounding/simulated_environment.py`. |
+| `godelOS/inference/modal/enhanced/` | An "Enhanced Modal Prover" beyond standard S4/S5 is referenced in the roadmap wiki but has no separate implementation file. The existing `ModalTableauProver` is activated. |
+
+## API Endpoints
+
+| Endpoint | Method | Description |
+|----------|--------|-------------|
+| `/api/status` | GET | System status – now includes `cognitive_subsystems` with per-subsystem status |
+| `/api/system/subsystems` | GET | Dedicated subsystem health endpoint – returns active/total counts and per-subsystem detail |
+
+## Smoke Tests
+
+`tests/test_cognitive_subsystem_activation.py` – 26 tests covering:
+
+- All 23 subsystems initialise without error
+- NLU pipeline processes text
+- Knowledge store has default contexts
+- Inference coordinator has all provers registered (incl. modal & CLP)
+- Symbol grounding components exist
+- Context engine creates / retrieves contexts
+- Common-sense manager is initialised
+- Learning system components exist (ILP, EBL, RL)
+- Metacognition manager can initialise sub-components
+- End-to-end data flow (NLU → KS → Inference → Context → NLG)
+- `GödelOSIntegration` exposes subsystem status via health endpoint