feat: market event

backend/routers/causal_lab.py

@@ -1127,9 +1127,9 @@ def _build_graph_json_from_spec(spec: dict) -> dict:
 
 def _run_auto_analysis(event: dict, template_id: int) -> bool:
     """
-    Lightweight causal analysis for the auto_template pipeline.
-    Builds inputs from event fields (no yfinance), evaluates the graph,
-    and upserts into causal_event_analyses so the instrument frise can read it.
+    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.
     """
     try:
         from services.database import get_conn
@@ -1220,9 +1220,27 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
         analyzed_at         = datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
         event_id            = event["id"]
 
+        # Effective lag from template edges (for price window and chip width)
+        edges = graph.get("edges", [])
+        effective_lag_days = max((e.get("lag_days", 0) or 0 for e in edges), default=0)
+
+        # Fetch actual prices to compute actual pips for scoring
+        actual_moves: dict = {}
+        drift_by_inst: dict = {}
+        try:
+            prices = _fetch_prices(event["start_date"], instruments, lag_days=effective_lag_days)
+            for inst in instruments:
+                drift = _drift_metrics(prices, event["start_date"], inst,
+                                       lag_min=0, lag_days=effective_lag_days)
+                drift_by_inst[inst] = drift
+                if drift.get("post_pips") is not None:
+                    actual_moves[inst] = drift["post_pips"]
+        except Exception as _pe:
+            logger.warning(f"[auto_analysis] price fetch failed for event #{event_id}: {_pe}")
+
         logger.info(
             f"[auto_analysis] event #{event_id} → tmpl #{template_id} | "
-            f"inputs={inputs} | instruments={all_instruments_csv}"
+            f"inputs={inputs} | instruments={all_instruments_csv} | actual_moves={actual_moves}"
         )
 
         existing = conn.execute(
@@ -1238,8 +1256,8 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
                 WHERE market_event_id=? AND template_id=?
             """, (
                 all_instruments_csv, json.dumps(inputs), json.dumps({}),
-                json.dumps(node_values), json.dumps({}), None,
-                json.dumps({}), analyzed_at,
+                json.dumps(node_values), json.dumps(actual_moves), None,
+                json.dumps(drift_by_inst), analyzed_at,
                 event_id, template_id,
             ))
         else:
@@ -1252,12 +1270,12 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
             """, (
                 event_id, template_id, all_instruments_csv,
                 json.dumps(inputs), json.dumps({}),
-                json.dumps(node_values), json.dumps({}),
-                None, json.dumps({}), analyzed_at,
+                json.dumps(node_values), json.dumps(actual_moves),
+                None, json.dumps(drift_by_inst), analyzed_at,
             ))
         conn.commit()
         conn.close()
-        logger.info(f"[auto_analysis] causal_event_analyses upserted → event #{event_id}, tmpl #{template_id}")
+        logger.info(f"[auto_analysis] upserted event #{event_id}, tmpl #{template_id}, actual_moves={actual_moves}")
         return True
 
     except Exception as e:
@@ -1369,6 +1387,49 @@ Règles : coef intermédiaire ∈ [-5,5] ; coef output en pips, |val| ∈ [30,20
         return {"error": str(e)}
 
 
+@router.post("/api/causal-lab/auto-analyze/refresh")
+def refresh_auto_analyses():
+    """
+    Re-run _run_auto_analysis for all causal_event_analyses rows with empty actual_json.
+    Fills in real price data so comprehension scores can be computed.
+    """
+    try:
+        from services.database import get_conn
+        conn = get_conn()
+        rows = conn.execute("""
+            SELECT a.id AS cea_id, a.market_event_id, a.template_id,
+                   a.actual_json
+            FROM causal_event_analyses a
+            WHERE a.actual_json IS NULL OR a.actual_json = '{}' OR a.actual_json = 'null'
+        """).fetchall()
+        conn.close()
+
+        refreshed, failed = 0, 0
+        for row in rows:
+            try:
+                conn2 = get_conn()
+                ev_row = conn2.execute(
+                    "SELECT * FROM market_events WHERE id = ?", (row["market_event_id"],)
+                ).fetchone()
+                conn2.close()
+                if not ev_row:
+                    continue
+                ok = _run_auto_analysis(dict(ev_row), row["template_id"])
+                if ok:
+                    refreshed += 1
+                else:
+                    failed += 1
+            except Exception as _e:
+                logger.warning(f"[refresh_auto_analyses] cea#{row['cea_id']}: {_e}")
+                failed += 1
+
+        logger.info(f"[refresh_auto_analyses] done: {refreshed} refreshed, {failed} failed")
+        return {"refreshed": refreshed, "failed": failed, "total": len(rows)}
+    except Exception as e:
+        logger.error(f"[refresh_auto_analyses] {e}")
+        raise HTTPException(500, str(e))
+
+
 @router.post("/api/causal-lab/create-from-event")
 def create_template_from_event(body: CreateFromEventRequest):
     """GPT-4o génère et enregistre un template causal adapté à l'événement."""

frontend/src/pages/InstrumentDashboard.tsx

@@ -1020,6 +1020,9 @@ function ExplanationScore({
   templates: CausalTemplate[]
   causalInsts: string[]
 }) {
+  const [refreshing, setRefreshing] = useState(false)
+  const [refreshDone, setRefreshDone] = useState(false)
+
   // For each linked event, compute the comprehension score and collect scored ones
   const scored: number[] = []
   const totalLinked: number[] = []
@@ -1051,6 +1054,19 @@ function ExplanationScore({
   const barCls = globalScore == null ? 'bg-slate-600'
     : globalScore >= 70 ? 'bg-emerald-500' : globalScore >= 40 ? 'bg-amber-500' : 'bg-red-500'
 
+  const handleRefresh = async () => {
+    setRefreshing(true)
+    try {
+      await api.post('/causal-lab/auto-analyze/refresh')
+      setRefreshDone(true)
+      setTimeout(() => setRefreshDone(false), 3000)
+    } finally {
+      setRefreshing(false)
+    }
+  }
+
+  const needsRefresh = totalLinked.length > 0 && scored.length === 0 && !refreshDone
+
   return (
     <div className="flex items-center gap-3 px-4 py-2.5 rounded-xl border border-slate-700/30 bg-dark-800/50">
       <span className="text-xs text-slate-500 whitespace-nowrap">Note globale</span>
@@ -1063,6 +1079,18 @@ function ExplanationScore({
       <span className="text-[10px] text-slate-600 whitespace-nowrap">
         {scored.length}/{totalLinked.length} graphes
       </span>
+      {needsRefresh && (
+        <button
+          onClick={handleRefresh}
+          disabled={refreshing}
+          className="text-[10px] text-violet-400 hover:text-violet-200 bg-violet-900/20 hover:bg-violet-900/40 border border-violet-800/40 rounded px-2 py-1 whitespace-nowrap disabled:opacity-50 transition-colors"
+        >
+          {refreshing ? '…' : 'Recalculer'}
+        </button>
+      )}
+      {refreshDone && (
+        <span className="text-[10px] text-emerald-500 whitespace-nowrap">✓ Rechargez la page</span>
+      )}
     </div>
   )
 }