fix: closes #1181

nexus/experience_store.py

@@ -5,6 +5,10 @@ SQLite-backed store for lived experiences only. The model remembers
 what it perceived, what it thought, and what it did — nothing else.
 
 Each row is one cycle of the perceive→think→act loop.
+
+Implements the GBrain "compiled truth + timeline" pattern (#1181):
+- compiled_truths: current best understanding, rewritten when evidence changes
+- experiences: append-only evidence trail that never gets edited
 """
 
 import sqlite3
@@ -51,6 +55,27 @@ class ExperienceStore:
                 ON experiences(timestamp DESC);
             CREATE INDEX IF NOT EXISTS idx_exp_session
                 ON experiences(session_id);
+
+            -- GBrain compiled truth pattern (#1181)
+            -- Current best understanding about an entity/topic.
+            -- Rewritten when new evidence changes the picture.
+            -- The timeline (experiences table) is the evidence trail — never edited.
+            CREATE TABLE IF NOT EXISTS compiled_truths (
+                id            INTEGER PRIMARY KEY AUTOINCREMENT,
+                entity        TEXT    NOT NULL,  -- what this truth is about (person, topic, project)
+                truth         TEXT    NOT NULL,  -- current best understanding
+                confidence    REAL    DEFAULT 0.5,  -- 0.0–1.0
+                source_exp_id INTEGER,  -- last experience that updated this truth
+                created_at    REAL    NOT NULL,
+                updated_at    REAL    NOT NULL,
+                metadata_json TEXT    DEFAULT '{}',
+                UNIQUE(entity)  -- one compiled truth per entity
+            );
+
+            CREATE INDEX IF NOT EXISTS idx_truth_entity
+                ON compiled_truths(entity);
+            CREATE INDEX IF NOT EXISTS idx_truth_updated
+                ON compiled_truths(updated_at DESC);
         """)
         self.conn.commit()
 
@@ -157,3 +182,117 @@ class ExperienceStore:
 
     def close(self):
         self.conn.close()
+
+    # ── GBrain compiled truth + timeline pattern (#1181) ────────────────
+
+    def upsert_compiled_truth(
+        self,
+        entity: str,
+        truth: str,
+        confidence: float = 0.5,
+        source_exp_id: Optional[int] = None,
+        metadata: Optional[dict] = None,
+    ) -> int:
+        """Create or update the compiled truth for an entity.
+
+        This is the 'compiled truth on top' from the GBrain pattern.
+        When new evidence changes our understanding, we rewrite this
+        record. The timeline (experiences table) preserves what led
+        here — it is never edited.
+
+        Args:
+            entity: What this truth is about (person, topic, project).
+            truth: Current best understanding.
+            confidence: 0.0–1.0 confidence score.
+            source_exp_id: Last experience ID that informed this truth.
+            metadata: Optional extra data as a dict.
+
+        Returns:
+            The row ID of the compiled truth.
+        """
+        now = time.time()
+        meta_json = json.dumps(metadata) if metadata else "{}"
+
+        self.conn.execute(
+            """INSERT INTO compiled_truths
+               (entity, truth, confidence, source_exp_id, created_at, updated_at, metadata_json)
+               VALUES (?, ?, ?, ?, ?, ?, ?)
+               ON CONFLICT(entity) DO UPDATE SET
+                   truth = excluded.truth,
+                   confidence = excluded.confidence,
+                   source_exp_id = excluded.source_exp_id,
+                   updated_at = excluded.updated_at,
+                   metadata_json = excluded.metadata_json""",
+            (entity, truth, confidence, source_exp_id, now, now, meta_json),
+        )
+        self.conn.commit()
+
+        row = self.conn.execute(
+            "SELECT id FROM compiled_truths WHERE entity = ?", (entity,)
+        ).fetchone()
+        return row[0]
+
+    def get_compiled_truth(self, entity: str) -> Optional[dict]:
+        """Get the current compiled truth for an entity."""
+        row = self.conn.execute(
+            """SELECT id, entity, truth, confidence, source_exp_id,
+                      created_at, updated_at, metadata_json
+               FROM compiled_truths WHERE entity = ?""",
+            (entity,),
+        ).fetchone()
+        if not row:
+            return None
+        return {
+            "id": row[0],
+            "entity": row[1],
+            "truth": row[2],
+            "confidence": row[3],
+            "source_exp_id": row[4],
+            "created_at": row[5],
+            "updated_at": row[6],
+            "metadata": json.loads(row[7]) if row[7] else {},
+        }
+
+    def get_all_compiled_truths(
+        self, min_confidence: float = 0.0, limit: int = 100
+    ) -> list[dict]:
+        """Get all compiled truths, optionally filtered by minimum confidence."""
+        rows = self.conn.execute(
+            """SELECT id, entity, truth, confidence, source_exp_id,
+                      created_at, updated_at, metadata_json
+               FROM compiled_truths
+               WHERE confidence >= ?
+               ORDER BY updated_at DESC
+               LIMIT ?""",
+            (min_confidence, limit),
+        ).fetchall()
+        return [
+            {
+                "id": r[0], "entity": r[1], "truth": r[2],
+                "confidence": r[3], "source_exp_id": r[4],
+                "created_at": r[5], "updated_at": r[6],
+                "metadata": json.loads(r[7]) if r[7] else {},
+            }
+            for r in rows
+        ]
+
+    def search_compiled_truths(self, query: str, limit: int = 10) -> list[dict]:
+        """Search compiled truths by entity name or truth content (LIKE match)."""
+        rows = self.conn.execute(
+            """SELECT id, entity, truth, confidence, source_exp_id,
+                      created_at, updated_at, metadata_json
+               FROM compiled_truths
+               WHERE entity LIKE ? OR truth LIKE ?
+               ORDER BY confidence DESC, updated_at DESC
+               LIMIT ?""",
+            (f"%{query}%", f"%{query}%", limit),
+        ).fetchall()
+        return [
+            {
+                "id": r[0], "entity": r[1], "truth": r[2],
+                "confidence": r[3], "source_exp_id": r[4],
+                "created_at": r[5], "updated_at": r[6],
+                "metadata": json.loads(r[7]) if r[7] else {},
+            }
+            for r in rows
+        ]