fix: update database queries to use 'template' instead of 'template_id' and adjust related references in ai_generate_plan function

supabase/functions/tests/ai-generate-plan-test.ts

@@ -53,7 +53,9 @@ Deno.test("ai_generate_plan creates plan and returns structured data", async ()
     .select("id")
     .limit(1)
     .single();
-  if (carreraError) throw new Error("Failed to fetch carrera: " + carreraError.message);
+  if (carreraError) {
+    throw new Error("Failed to fetch carrera: " + carreraError.message);
+  }
   if (!carrera) throw new Error("No carrera found");
 
   const datosBasicos = {
@@ -94,38 +96,49 @@ Deno.test("ai_generate_plan creates plan and returns structured data", async ()
   );
   assertEquals(data.plan_datos.duracion_del_ciclo_escolar, "16"); // Semestre -> 16
 });
-/*
-Deno.test("ai-structured (multipart + file)", async () => {
+
+Deno.test("ai_generate_plan (multipart with files)", async () => {
   const { client, accessToken } = await getAuthedClient();
 
-  // Lee un PDF local (ajusta path)
-  const bytes = await Deno.readFile("files/carta.pdf");
-  const file = new File([bytes], "carta.pdf", { type: "application/pdf" });
+  const { data: carrera, error: carreraError } = await client
+    .from("carreras")
+    .select("id")
+    .limit(1)
+    .single();
+  if (carreraError) {
+    throw new Error("Failed to fetch carrera: " + carreraError.message);
+  }
+  if (!carrera) throw new Error("No carrera found");
+
+  const datosBasicos = {
+    nombrePlan: "Plan de estudios generado con referencias",
+    carreraId: carrera.id,
+    nivel: "Maestría",
+    tipoCiclo: "Semestre",
+    numCiclos: 4,
+  };
+
+  const iaConfig = {
+    descripcionEnfoque: "Programa de postgrado enfocado en tecnología",
+    notasAdicionales: "Considerar tendencias actuales en IA",
+  };
+
+  // Create a simple test file
+  const fileContent = "Sample curriculum reference document";
+  const file = new File([fileContent], "reference.txt", { type: "text/plain" });
 
   const payload = {
-    response: { input: "Resume estos documentos en JSON.", model: "gpt-5" },
-    structured: {
-      type: "json_schema",
-      name: "resumen",
-      strict: true,
-      schema: {
-        type: "object",
-        properties: { resumen: { type: "string" } },
-        required: ["resumen"],
-        additionalProperties: false,
-      },
-    },
-    storage: { prefix: "tmp" },
+    datosBasicos,
+    iaConfig,
   };
 
   const fd = new FormData();
   fd.append("payload", JSON.stringify(payload));
   fd.append("files", file);
 
-  const { data, error } = await client.functions.invoke("ai-structured", {
+  const { data, error } = await client.functions.invoke("ai_generate_plan", {
     headers: {
-      Authorization: `Bearer ${accessToken}`, // 👈 necesario
-      // NO pongas Content-Type: fetch lo setea con boundary para FormData ✅
+      Authorization: `Bearer ${accessToken}`,
     },
     method: "POST",
     body: fd,
@@ -135,10 +148,11 @@ Deno.test("ai-structured (multipart + file)", async () => {
   assert(data, "Expected data from function");
 
   assertEquals(data.ok, true);
-  assert(typeof data.output?.resumen === "string");
-  assert(data.output.resumen.length > 0);
+  assert(data.plan);
+  assertEquals(data.plan.nombre, datosBasicos.nombrePlan);
+  assertEquals(data.plan.nivel, "Maestría");
+  assertEquals(data.plan.numero_ciclos, datosBasicos.numCiclos);
 
-  // opcional: valida que registró upload(s) a storage
-  assert(Array.isArray(data.references?.uploadedToStorage));
+  assert(data.references);
+  assertEquals(data.references.tempFilesCount, 1);
 });
- */