Add basic version: SemIf decision engine, urgency queue, skill tree, skill loop, decision log, dream pass, CLI

semif_agent/log.py

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+"""Decision logging: every SemIf call is written as a labeled training row.
+
+Rows match the SemIf `decisions.jsonl` shape plus the prediction-observation
+cost fields. `observed_outcome` is the label for the cost function; by default
+it is the option that was actually selected (self-consistent), and a human
+override can relabel a row to the correct outcome with a higher weight.
+"""
+
+from __future__ import annotations
+
+import json
+import time
+from pathlib import Path
+
+from .decisions import DecisionRequest, DecisionResult
+
+
+class DecisionLog:
+    def __init__(self, path: str = "data/decisions.jsonl"):
+        self.path = Path(path)
+
+    def append(
+        self,
+        request: DecisionRequest,
+        result: DecisionResult,
+        label: str | None = None,
+        extra: dict | None = None,
+    ) -> None:
+        """Append one decision row. `label` overrides observed_outcome."""
+        observed = label if label is not None else result.selected
+        source = "human" if label is not None else "self"
+        row = {
+            "id": request.id,
+            "ts": time.time(),
+            "state": request.state,
+            "question": request.question,
+            "options": [{"id": o.id, "description": o.description} for o in request.options],
+            "predicted_probs": result.probs,
+            "selected": result.selected,
+            "observed_outcome": observed,
+            "label_source": source,
+        }
+        if extra:
+            row["extra"] = extra
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        with self.path.open("a") as handle:
+            handle.write(json.dumps(row) + "\n")
+
+    def relabel(self, decision_id: str, observed: str) -> bool:
+        """Human override: set a corrected observed outcome for one row."""
+        rows = self.read()
+        found = False
+        for row in rows:
+            if row["id"] == decision_id:
+                row["observed_outcome"] = observed
+                row["label_source"] = "human"
+                found = True
+        if not found:
+            return False
+        self._write(rows)
+        return True
+
+    def read(self) -> list[dict]:
+        if not self.path.is_file():
+            return []
+        rows = []
+        with self.path.open("r") as handle:
+            for line in handle:
+                line = line.strip()
+                if line:
+                    rows.append(json.loads(line))
+        return rows
+
+    def _write(self, rows: list[dict]) -> None:
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        with self.path.open("w") as handle:
+            for row in rows:
+                handle.write(json.dumps(row) + "\n")