Add ReflectionEngine

src/timmy/reflection.py

@@ -0,0 +1,82 @@
+
+import logging
+from datetime import UTC, datetime, timedelta
+from typing import List, Optional
+
+from sqlalchemy.orm import Session
+from dashboard.models.database import SessionLocal
+from dashboard.models.calm import Task, JournalEntry
+from dashboard.models.reflection import Reflection
+from integrations.llm.ollama import query_ollama
+
+logger = logging.getLogger(__name__)
+
+class ReflectionEngine:
+    """Engine for Timmy's self-reflection loop."""
+
+    async def reflect_once(self) -> Optional[Reflection]:
+        """Review recent activity and generate a reflection."""
+        logger.info("Starting self-reflection cycle...")
+        
+        db = SessionLocal()
+        try:
+            # 1. Gather context
+            now = datetime.now(UTC)
+            since = now - timedelta(hours=24)
+            
+            recent_tasks = db.query(Task).filter(Task.updated_at >= since).all()
+            recent_journal = db.query(JournalEntry).filter(JournalEntry.created_at >= since).first()
+            
+            # 2. Build prompt
+            context = f"Recent Tasks: {[t.title for t in recent_tasks]}\n"
+            if recent_journal:
+                context += f"Journal: {recent_journal.evening_reflection}\n"
+            
+            prompt = f"""
+            You are Timmy, an AI agent. Review your recent activity and provide a short, insightful self-reflection.
+            Focus on what you've achieved, what you've missed, and how you're feeling about your current progress.
+            
+            Context:
+            {context}
+            
+            Output format:
+            Reflection: [Your reflection text]
+            Sentiment: [positive/neutral/negative]
+            Focus Area: [e.g., Productivity, Health, Learning]
+            """
+            
+            # 3. Query LLM
+            response = await query_ollama(prompt)
+            
+            # 4. Parse and save
+            reflection_text = ""
+            sentiment = "neutral"
+            focus_area = "General"
+            
+            for line in response.split("\n"):
+                if line.startswith("Reflection:"):
+                    reflection_text = line.replace("Reflection:", "").strip()
+                elif line.startswith("Sentiment:"):
+                    sentiment = line.replace("Sentiment:", "").strip().lower()
+                elif line.startswith("Focus Area:"):
+                    focus_area = line.replace("Focus Area:", "").strip()
+            
+            if reflection_text:
+                reflection = Reflection(
+                    content=reflection_text,
+                    sentiment=sentiment,
+                    focus_area=focus_area
+                )
+                db.add(reflection)
+                db.commit()
+                db.refresh(reflection)
+                logger.info("Self-reflection saved: %s", reflection_text[:50])
+                return reflection
+                
+        except Exception as exc:
+            logger.error("Reflection error: %s", exc)
+        finally:
+            db.close()
+        return None
+
+reflection_engine = ReflectionEngine()