Update src/components/ai_core_identityscan.py

src/components/ai_core_identityscan.py

@@ -1,111 +1,111 @@
-"""Lightweight AI core for identity scanning and analysis.
-
-This module provides a compact, dependency-safe `AICore` class used by
-other components. The original file contained merge markers and
-incomplete code; this replacement focuses on providing functioning
-interfaces (async `generate_response`, `shutdown`) and uses existing
-local components where available.
-"""
-from typing import Any, Dict, List, Optional
-import asyncio
-import json
-import logging
-import os
-
-from components.multimodal_analyzer import MultimodalAnalyzer
-from components.dynamic_learning import DynamicLearner
-from components.health_monitor import HealthMonitor
-
-try:
-    from utils.logger import logger
-except Exception:
-    logger = logging.getLogger(__name__)
-
-
-class AICore:
-    """Minimal, safe AICore replacement for identity scanning workflows."""
-
-    def __init__(self, config_path: str = "config.json"):
-        self.config = self._load_config(config_path)
-        self.multimodal = MultimodalAnalyzer()
-        self.learner = DynamicLearner()
-        self.health = HealthMonitor()
-        self._initialized = False
-
-    def _load_config(self, path: str) -> Dict[str, Any]:
-        if not path or not os.path.exists(path):
-            return {}
-        try:
-            with open(path, "r", encoding="utf-8") as f:
-                return json.load(f)
-        except Exception:
-            return {}
-
-    async def initialize(self) -> bool:
-        """Initialize async subsystems (e.g., health monitor)."""
-        try:
-            ok = await self.health.initialize()
-            self._initialized = ok
-            return ok
-        except Exception as e:
-            logger.exception("Failed to initialize AICore: %s", e)
-            return False
-
-    async def generate_response(self, user_id: int, query: str, multimodal_input: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
-        """Produce a safe, explainable response using local subsystems.
-
-        - Runs a lightweight analysis of any multimodal input
-        - Updates the dynamic learner with a summary of the interaction
-        - Returns a dict containing analysis and a text response
-        """
-        try:
-            analyses = {}
-            if multimodal_input:
-                analyses = self.multimodal.analyze_content(multimodal_input)
-
-            # Simple content-based reply
-            text_summary = ""
-            if "text" in analyses:
-                t = analyses["text"]
-                text_summary = f"Received text: length={t.get('length')} words={t.get('word_count')}"
-            else:
-                text_summary = f"Query received: {query[:200]}"
-
-            # Update learner with a compact interaction record
-            adaptation_score = self.learner.update({
-                "user_id": user_id,
-                "query_summary": text_summary,
-                "multimodal_modalities": list(analyses.keys())
-            })
-
-            # Health snapshot
-            health_status = self.health.get_health_summary()
-
-            response_text = f"Acknowledged. Adaptation score={adaptation_score:.2f}."
-
-            return {
-                "response": response_text,
-                "analysis": analyses,
-                "adaptation_score": adaptation_score,
-                "health": health_status,
-            }
-        except Exception as e:
-            logger.exception("generate_response failed: %s", e)
-            return {"error": "internal_error", "detail": str(e)}
-
-    async def shutdown(self):
-        """Clean up resources if necessary."""
-        # HealthMonitor has no async shutdown but we keep the method for parity.
-        await asyncio.sleep(0)
-
-
-# Module quick test when run directly
-if __name__ == "__main__":
-    async def _test():
-        core = AICore()
-        await core.initialize()
-        out = await core.generate_response(1, "Hello world", {"text": "Hello world from test"})
-        print(out)
-        await core.shutdown()
-
+"""Lightweight AI core for identity scanning and analysis.
+
+This module provides a compact, dependency-safe `AICore` class used by
+other components. The original file contained merge markers and
+incomplete code; this replacement focuses on providing functioning
+interfaces (async `generate_response`, `shutdown`) and uses existing
+local components where available.
+"""
+from typing import Any, Dict, List, Optional
+import asyncio
+import json
+import logging
+import os
+
+from .multimodal_analyzer import MultimodalAnalyzer
+from .dynamic_learning import DynamicLearner
+from .health_monitor import HealthMonitor
+
+try:
+    from utils.logger import logger
+except Exception:
+    logger = logging.getLogger(__name__)
+
+
+class AICore:
+    """Minimal, safe AICore replacement for identity scanning workflows."""
+
+    def __init__(self, config_path: str = "config.json"):
+        self.config = self._load_config(config_path)
+        self.multimodal = MultimodalAnalyzer()
+        self.learner = DynamicLearner()
+        self.health = HealthMonitor()
+        self._initialized = False
+
+    def _load_config(self, path: str) -> Dict[str, Any]:
+        if not path or not os.path.exists(path):
+            return {}
+        try:
+            with open(path, "r", encoding="utf-8") as f:
+                return json.load(f)
+        except Exception:
+            return {}
+
+    async def initialize(self) -> bool:
+        """Initialize async subsystems (e.g., health monitor)."""
+        try:
+            ok = await self.health.initialize()
+            self._initialized = ok
+            return ok
+        except Exception as e:
+            logger.exception("Failed to initialize AICore: %s", e)
+            return False
+
+    async def generate_response(self, user_id: int, query: str, multimodal_input: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+        """Produce a safe, explainable response using local subsystems.
+
+        - Runs a lightweight analysis of any multimodal input
+        - Updates the dynamic learner with a summary of the interaction
+        - Returns a dict containing analysis and a text response
+        """
+        try:
+            analyses = {}
+            if multimodal_input:
+                analyses = self.multimodal.analyze_content(multimodal_input)
+
+            # Simple content-based reply
+            text_summary = ""
+            if "text" in analyses:
+                t = analyses["text"]
+                text_summary = f"Received text: length={t.get('length')} words={t.get('word_count')}"
+            else:
+                text_summary = f"Query received: {query[:200]}"
+
+            # Update learner with a compact interaction record
+            adaptation_score = self.learner.update({
+                "user_id": user_id,
+                "query_summary": text_summary,
+                "multimodal_modalities": list(analyses.keys())
+            })
+
+            # Health snapshot
+            health_status = self.health.get_health_summary()
+
+            response_text = f"Acknowledged. Adaptation score={adaptation_score:.2f}."
+
+            return {
+                "response": response_text,
+                "analysis": analyses,
+                "adaptation_score": adaptation_score,
+                "health": health_status,
+            }
+        except Exception as e:
+            logger.exception("generate_response failed: %s", e)
+            return {"error": "internal_error", "detail": str(e)}
+
+    async def shutdown(self):
+        """Clean up resources if necessary."""
+        # HealthMonitor has no async shutdown but we keep the method for parity.
+        await asyncio.sleep(0)
+
+
+# Module quick test when run directly
+if __name__ == "__main__":
+    async def _test():
+        core = AICore()
+        await core.initialize()
+        out = await core.generate_response(1, "Hello world", {"text": "Hello world from test"})
+        print(out)
+        await core.shutdown()
+
     asyncio.run(_test())