debug: expose full inputs/outputs in Recalculer response for diagnosis

_run_auto_analysis now returns a rich dict {ok, inputs, node_values, actual_moves, error}
instead of bool. The refresh endpoint captures and forwards:
- inputs: what values were fed to evaluate_graph
- node_keys: which nodes were computed in prediction
- actual_moves: actual price pips fetched
- run_error: exception message if it failed

Frontend shows all of this after clicking Recalculer so the root cause is visible.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/routers/causal_lab.py

@@ -1127,11 +1127,10 @@ def _build_graph_json_from_spec(spec: dict) -> dict:
     }
 
 
-def _run_auto_analysis(event: dict, template_id: int) -> bool:
+def _run_auto_analysis(event: dict, template_id: int) -> dict:
     """
     Causal analysis for the auto_template pipeline.
-    Builds inputs from event fields, evaluates the graph, fetches actual prices,
-    and upserts into causal_event_analyses so the instrument frise can score it.
+    Returns {"ok": bool, "inputs": dict, "node_values": dict, "actual_moves": dict, "error": str}.
     """
     try:
         from services.database import get_conn
@@ -1142,7 +1141,7 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
         if not tmpl:
             conn.close()
             logger.warning(f"[auto_analysis] template #{template_id} introuvable")
-            return False
+            return {"ok": False, "error": f"template #{template_id} introuvable"}
 
         graph   = tmpl["graph_json"]
         inputs  = {}
@@ -1310,11 +1309,17 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
         conn.commit()
         conn.close()
         logger.info(f"[auto_analysis] upserted event #{event_id}, tmpl #{template_id}, actual_moves={actual_moves}")
-        return True
+        return {
+            "ok": True,
+            "inputs": inputs,
+            "node_values": node_values,
+            "actual_moves": actual_moves,
+            "instruments": instruments,
+        }
 
     except Exception as e:
-        logger.error(f"[auto_analysis] event #{event.get('id')}: {e}")
-        return False
+        logger.error(f"[auto_analysis] event #{event.get('id')}: {e}", exc_info=True)
+        return {"ok": False, "error": str(e)}
 
 
 def auto_assign_template(event_id: int) -> dict:
@@ -1481,13 +1486,16 @@ def refresh_auto_analyses():
                 detail["actual_value"]    = ev.get("actual_value")
                 detail["expected_value"]  = ev.get("expected_value")
                 detail["start_date"]      = ev.get("start_date")
-                ok = _run_auto_analysis(ev, row["template_id"])
-                detail["result"] = "ok" if ok else "failed"
-                if ok:
+                res = _run_auto_analysis(ev, row["template_id"])
+                detail["result"]         = "ok" if res["ok"] else "failed"
+                detail["inputs"]         = res.get("inputs", {})
+                detail["node_keys"]      = list(res.get("node_values", {}).keys())
+                detail["actual_moves"]   = res.get("actual_moves", {})
+                detail["run_error"]      = res.get("error")
+                if res["ok"]:
                     refreshed += 1
                 else:
                     failed += 1
-                    detail["result"] = "run_returned_false"
             except Exception as _e:
                 logger.warning(f"[refresh_auto_analyses] cea#{row['cea_id']}: {_e}")
                 detail["result"] = f"exception: {_e}"