Use Terra and Luna for task-specific AI processing

backend/src/modules/email/email.entity-suggestions.ts

@@ -71,7 +71,8 @@ export async function suggestEmailEntities(message: any, allCandidates: EntityCa
     const candidates = selectCandidates(allCandidates, JSON.stringify(mail))
     if (!candidates.length) return []
     const request: any = {
-        model: "gpt-4o",
+        model: "gpt-5.6-luna",
+        reasoning_effort: "none",
         store: false,
         max_completion_tokens: 1500,
         response_format: zodResponseFormat(suggestionFormat as any, "email_entity_suggestions"),

backend/src/utils/gpt.ts

@@ -168,7 +168,8 @@ export const getInvoiceDataFromGPT = async function (
 
 
     const completionRequest: any = {
-        model: "gpt-4o",
+        model: "gpt-5.6-terra",
+        reasoning_effort: "low",
         store: true,
         response_format: zodResponseFormat(InstructionFormat as any, "instruction"),
         messages: [

backend/src/utils/liquidityForecast.ts

@@ -407,7 +407,8 @@ const detectRecurringWithAi = async (server: FastifyInstance, statements: any[])
 
     try {
         const completionRequest: any = {
-            model: "gpt-4o",
+            model: "gpt-5.6-terra",
+            reasoning_effort: "low",
             store: true,
             response_format: zodResponseFormat(AiRecurringFormat as any, "liquidity_recurring_transactions"),
             messages: [

push-server/apps/api/src/routes/services.ts

@@ -5,7 +5,7 @@ import { requireInstance } from "../lib/auth.js";
 import { recordServiceUsage, requireCentralService } from "../services/central-services.js";
 
 const aiSchema = z.object({
-  model: z.enum(["gpt-4o", "gpt-4o-mini"]),
+  model: z.enum(["gpt-4o", "gpt-4o-mini", "gpt-5.6-terra", "gpt-5.6-luna"]),
   messages: z.array(z.object({
     role: z.enum(["system", "user", "assistant"]),
     content: z.union([z.string(), z.array(z.unknown())]),