feat: pressure

backend/services/guidance_sync.py

@@ -96,18 +96,33 @@ def _find_existing(conn, currency: str, meeting_date: str) -> Optional[dict]:
 def _upsert_analyses(conn, event_id: int, template_id: int, instruments: list[str], signal: float):
     """
     Crée/recrée les causal_event_analyses pour que l'event apparaisse
-    dans la Frise de chaque instrument concerné.
+    dans la Frise et dans la theoretical-curve de chaque instrument.
+    Calcule prediction_json via evaluate_graph pour alimenter le factor engine.
     """
     conn.execute(
         "DELETE FROM causal_event_analyses WHERE market_event_id=?", (event_id,)
     )
-    inputs = json.dumps({"guidance_signal": signal})
+    inputs_dict = {"guidance_signal": signal}
+    inputs_json = json.dumps(inputs_dict)
+
+    # Évalue le graphe pour obtenir les pips prédits par instrument
+    node_values: dict = {}
+    try:
+        from services.causal_graphs import evaluate_graph, get_template
+        tmpl = get_template(conn, template_id)
+        if tmpl:
+            node_values = evaluate_graph(tmpl["graph_json"], inputs_dict)
+    except Exception as e:
+        logger.warning(f"[guidance_sync] evaluate_graph failed: {e}")
+
+    prediction_json = json.dumps(node_values) if node_values else None
+
     for inst in instruments:
         conn.execute("""
             INSERT INTO causal_event_analyses
-                (market_event_id, template_id, instrument, inputs_json, analyzed_at)
-            VALUES (?, ?, ?, ?, datetime('now'))
-        """, (event_id, template_id, inst, inputs))
+                (market_event_id, template_id, instrument, inputs_json, prediction_json, analyzed_at)
+            VALUES (?, ?, ?, ?, ?, datetime('now'))
+        """, (event_id, template_id, inst, inputs_json, prediction_json))
 
 
 def _build_title(currency: str, signal: float, meeting_date: str) -> str: