Update app.py

app.py

@@ -29,12 +29,19 @@ def evaluate_trajectory_api(api_key: str, payload_json: str) -> str:
     except Exception as e:
         return json.dumps({"error": f"Malformed JSON: {e}", "status_code": 400})
 
-    # 1. Calcul rapid
-    report = evaluate_trajectories_batch(raw_payload, "standard", False)
+    # AFLAM PLANUL UTILIZATORULUI DIN SUPABASE (ex: "free" sau "pro")
+    user_plan = auth_ctx.get("plan", "free")
+
+    # Trimitem planul catre functia de evaluare
+    report = evaluate_trajectories_batch(raw_payload, "standard", False, plan=user_plan)
+
+    # Daca a depasit limita de pasi pe free tier, returnam eroarea
+    if "error" in report:
+        return json.dumps(report)
+
     ai_markdown = generate_ai_report(report)
     report["narrative_report"] = ai_markdown
 
-    # 2. Salvarea in DB se face pe fundal (non-blocking pentru utilizator!)
     if auth_ctx.get("project_id"):
         t = threading.Thread(
             target=save_evaluation_to_db, 
@@ -43,10 +50,10 @@ def evaluate_trajectory_api(api_key: str, payload_json: str) -> str:
         )
         t.start()
 
-    # 3. Returneaza instant rezultatul la client!
     return json.dumps(report)
 
 
+
 with gr.Blocks(title="Limina AI Engine") as demo:
     gr.Markdown("# Limina AI — Cognitive Trajectory Engine API")
     api_key_input = gr.Textbox(label="API Key", type="password")