Add offline monthly insights with Ollama

openspec/changes/monthly-expense-tracker-v1/tasks.md

@@ -22,8 +22,8 @@
 
 - [x] 4.1 Implement monthly dashboard aggregation services for totals, category breakdowns, and derived comparisons.
 - [x] 4.2 Implement the dashboard API route and render dashboard sections for month-to-date metrics and comparisons.
-- [ ] 4.3 Implement the offline `Ollama` insight service with structured monthly snapshot input and sparse-month fallback logic.
+- [x] 4.3 Implement the offline `Ollama` insight service with structured monthly snapshot input and sparse-month fallback logic.
-- [ ] 4.4 Implement insight generation and display in the dashboard, including persisted monthly insight records and offline-runtime fallback messaging.
+- [x] 4.4 Implement insight generation and display in the dashboard, including persisted monthly insight records and offline-runtime fallback messaging.
 
 ## 5. Offline categorization
 
@@ -35,4 +35,4 @@
 ## 6. Verification
 
 - [ ] 6.1 Add automated tests for validation, persistence, dashboard aggregates, offline insight fallback behavior, and category suggestion rules.
-- [ ] 6.2 Verify the primary user flows in the browser, including expense entry, paycheck entry, dashboard updates, category suggestion, and insight generation.
+- [x] 6.2 Verify the primary user flows in the browser, including expense entry, paycheck entry, dashboard updates, category suggestion, and insight generation.

package-lock.json

@@ -10,7 +10,6 @@
       "dependencies": {
         "@prisma/client": "^6.6.0",
         "next": "16.2.1",
-        "openai": "^5.10.2",
         "react": "19.2.4",
         "react-dom": "19.2.4",
         "recharts": "^2.15.4",
@@ -6854,27 +6853,6 @@
       "devOptional": true,
       "license": "MIT"
     },
-    "node_modules/openai": {
-      "version": "5.23.2",
-      "resolved": "https://registry.npmjs.org/openai/-/openai-5.23.2.tgz",
-      "integrity": "sha512-MQBzmTulj+MM5O8SKEk/gL8a7s5mktS9zUtAkU257WjvobGc9nKcBuVwjyEEcb9SI8a8Y2G/mzn3vm9n1Jlleg==",
-      "license": "Apache-2.0",
-      "bin": {
-        "openai": "bin/cli"
-      },
-      "peerDependencies": {
-        "ws": "^8.18.0",
-        "zod": "^3.23.8"
-      },
-      "peerDependenciesMeta": {
-        "ws": {
-          "optional": true
-        },
-        "zod": {
-          "optional": true
-        }
-      }
-    },
     "node_modules/optionator": {
       "version": "0.9.4",
       "resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.4.tgz",
@@ -8435,6 +8413,7 @@
       "integrity": "sha512-w+N7Hifpc3gRjZ63vYBXA56dvvRlNWRczTdmCBBa+CotUzAPf5b7YMdMR/8CQoeYE5LX3W4wj6RYTgonm1b9DA==",
       "dev": true,
       "license": "MIT",
+      "peer": true,
       "dependencies": {
         "esbuild": "^0.27.0",
         "fdir": "^6.5.0",

package.json

@@ -15,7 +15,6 @@
   "dependencies": {
     "@prisma/client": "^6.6.0",
     "next": "16.2.1",
-    "openai": "^5.10.2",
     "react": "19.2.4",
     "react-dom": "19.2.4",
     "recharts": "^2.15.4",

prisma/migrations/20260323133000_add_monthly_insight_unique/migration.sql

@@ -0,0 +1,3 @@
+-- CreateIndex
+CREATE UNIQUE INDEX "MonthlyInsight_month_key" ON "MonthlyInsight"("month");
+

prisma/schema.prisma

@@ -36,7 +36,7 @@ model Paycheck {
 
 model MonthlyInsight {
   id              String   @id @default(cuid())
-  month           String
+  month           String   @unique
   year            Int
   generatedAt     DateTime @default(now())
   summary         String

src/app/insights/generate/route.ts

@@ -0,0 +1,21 @@
+import { NextResponse } from "next/server";
+
+import { getCurrentMonthKey } from "@/lib/date";
+import { generateMonthlyInsight } from "@/lib/insights";
+import { monthQuerySchema } from "@/lib/validation";
+
+export async function POST(request: Request) {
+  const url = new URL(request.url);
+  const rawMonth = url.searchParams.get("month") ?? getCurrentMonthKey();
+  const parsed = monthQuerySchema.safeParse({ month: rawMonth });
+
+  if (!parsed.success) {
+    return NextResponse.json(
+      { error: parsed.error.issues[0]?.message ?? "Invalid insight month." },
+      { status: 400 },
+    );
+  }
+
+  const result = await generateMonthlyInsight(parsed.data.month);
+  return NextResponse.json(result);
+}

src/components/home-dashboard.tsx

@@ -9,6 +9,11 @@ import { formatCurrencyFromCents, formatPercent } from "@/lib/money";
 
 type DashboardSnapshot = {
   month: string;
+  insight: {
+    summary: string;
+    recommendations: string;
+    generatedAt: string;
+  } | null;
   totals: {
     expensesCents: number;
     paychecksCents: number;
@@ -29,22 +34,27 @@ export function HomeDashboard() {
   const [selectedMonth, setSelectedMonth] = useState(getCurrentMonthKey());
   const [snapshot, setSnapshot] = useState<DashboardSnapshot | null>(null);
   const [error, setError] = useState<string | null>(null);
+  const [insightBusy, setInsightBusy] = useState(false);
 
-  useEffect(() => {
+  async function loadDashboard(month: string) {
-    async function loadDashboard() {
+    const response = await fetch(`/dashboard?month=${month}`, { cache: "no-store" });
-      const response = await fetch(`/dashboard?month=${selectedMonth}`, { cache: "no-store" });
+    const payload = (await response.json()) as DashboardSnapshot & { error?: string };
-      const payload = (await response.json()) as DashboardSnapshot & { error?: string };
 
-      if (!response.ok) {
+    if (!response.ok) {
-        setError(payload.error ?? "Could not load the dashboard.");
+      setError(payload.error ?? "Could not load the dashboard.");
-        return;
+      return;
-      }
-
-      setError(null);
-      setSnapshot(payload);
     }
 
-    void loadDashboard();
+    setError(null);
+    setSnapshot(payload);
+  }
+
+  useEffect(() => {
+    const timeoutId = window.setTimeout(() => {
+      void loadDashboard(selectedMonth);
+    }, 0);
+
+    return () => window.clearTimeout(timeoutId);
   }, [selectedMonth]);
 
   const topCategoryLabel = useMemo(() => {
@@ -60,6 +70,22 @@ export function HomeDashboard() {
       ? "No spend yet"
       : formatPercent(snapshot.totals.paycheckCoverageRatio);
 
+  async function handleGenerateInsights() {
+    setInsightBusy(true);
+
+    const response = await fetch(`/insights/generate?month=${selectedMonth}`, { method: "POST" });
+    const payload = (await response.json().catch(() => null)) as { error?: string } | null;
+
+    setInsightBusy(false);
+
+    if (!response.ok) {
+      setError(payload?.error ?? "Could not generate insights.");
+      return;
+    }
+
+    await loadDashboard(selectedMonth);
+  }
+
   return (
     <div className="space-y-10">
       <section className="grid gap-6 rounded-[2rem] border border-stone-200 bg-[radial-gradient(circle_at_top_left,_rgba(251,191,36,0.26),_transparent_32%),linear-gradient(135deg,#fffaf2,#f3efe7)] p-8 shadow-[0_28px_70px_rgba(120,90,50,0.10)] lg:grid-cols-[1.2fr_0.8fr]">
@@ -119,6 +145,43 @@ export function HomeDashboard() {
         </div>
       </section>
 
+      <section className="rounded-[2rem] border border-stone-200 bg-white p-8 shadow-[0_24px_60px_rgba(120,90,50,0.08)]">
+        <div className="flex flex-wrap items-center justify-between gap-4">
+          <div>
+            <p className="text-sm font-semibold uppercase tracking-[0.24em] text-stone-500">Private monthly insight</p>
+            <h2 className="mt-2 text-3xl font-semibold text-stone-950">Offline guidance for this month</h2>
+          </div>
+          <button
+            type="button"
+            onClick={() => void handleGenerateInsights()}
+            disabled={insightBusy}
+            className="rounded-full bg-stone-950 px-5 py-3 text-sm font-semibold text-white transition hover:bg-stone-800 disabled:cursor-not-allowed disabled:bg-stone-400"
+          >
+            {insightBusy ? "Generating..." : "Generate insights"}
+          </button>
+        </div>
+
+        {snapshot?.insight ? (
+          <div className="mt-6 grid gap-4 lg:grid-cols-[1.2fr_0.8fr]">
+            <article className="rounded-3xl border border-stone-200 bg-[#fffcf7] px-5 py-5">
+              <p className="text-xs uppercase tracking-[0.2em] text-stone-500">Summary</p>
+              <p className="mt-3 text-base leading-7 text-stone-700">{snapshot.insight.summary}</p>
+            </article>
+            <article className="rounded-3xl border border-stone-200 bg-[#f8faf7] px-5 py-5">
+              <p className="text-xs uppercase tracking-[0.2em] text-stone-500">Next month guidance</p>
+              <p className="mt-3 text-base leading-7 text-stone-700">{snapshot.insight.recommendations}</p>
+              <p className="mt-4 text-xs uppercase tracking-[0.2em] text-stone-400">
+                Generated {new Date(snapshot.insight.generatedAt).toLocaleString()}
+              </p>
+            </article>
+          </div>
+        ) : (
+          <div className="mt-6 rounded-3xl border border-dashed border-stone-300 px-5 py-8 text-stone-600">
+            No saved insight for this month yet. Generate one to get a private offline summary.
+          </div>
+        )}
+      </section>
+
       <section className="grid gap-6 lg:grid-cols-[1.1fr_0.9fr]">
         <div className="rounded-[2rem] border border-stone-200 bg-white p-8 shadow-[0_24px_60px_rgba(120,90,50,0.08)]">
           <div className="flex items-center justify-between gap-4">

src/lib/category-suggestion.ts

@@ -1,4 +1,5 @@
 import { CATEGORY_VALUES, type CategoryValue } from "@/lib/categories";
+import { generateOllamaJson } from "@/lib/ollama";
 
 type SuggestionSource = "rule" | "model" | "unavailable";
 
@@ -75,25 +76,11 @@ export async function suggestCategoryForMerchant(merchantName: string): Promise<
   }
 
   try {
-    const response = await fetch(`${process.env.OLLAMA_URL ?? "http://127.0.0.1:11434"}/api/generate`, {
+    const parsed = await generateOllamaJson<{ category?: string }>({
-      method: "POST",
+      prompt:
-      headers: { "Content-Type": "application/json" },
+        "You categorize personal expense merchants. Return JSON with one key named category. Allowed values only: RENT, FOOD, TRANSPORT, BILLS, SHOPPING, HEALTH, ENTERTAINMENT, MISC. Merchant: " +
-      body: JSON.stringify({
+        normalized,
-        model: process.env.OLLAMA_MODEL ?? "qwen2.5:7b",
-        format: "json",
-        stream: false,
-        prompt:
-          "You categorize personal expense merchants. Return JSON with one key named category. Allowed values only: RENT, FOOD, TRANSPORT, BILLS, SHOPPING, HEALTH, ENTERTAINMENT, MISC. Merchant: " +
-          normalized,
-      }),
     });
-
-    if (!response.ok) {
-      throw new Error(`Ollama request failed with ${response.status}`);
-    }
-
-    const payload = (await response.json()) as { response?: string };
-    const parsed = payload.response ? JSON.parse(payload.response) : null;
     const category = parseSuggestedCategory(parsed?.category);
 
     if (!category) {

src/lib/dashboard.test.ts

@@ -32,6 +32,7 @@ describe("buildDashboardSnapshot", () => {
           createdAt: new Date("2026-03-01T10:00:00Z"),
         },
       ],
+      insight: null,
     });
 
     expect(snapshot.totals.expensesCents).toBe(123200);
@@ -48,6 +49,7 @@ describe("buildDashboardSnapshot", () => {
       month: "2026-03",
       expenses: [],
       paychecks: [],
+      insight: null,
     });
 
     expect(snapshot.totals.expensesCents).toBe(0);
@@ -55,5 +57,6 @@ describe("buildDashboardSnapshot", () => {
     expect(snapshot.totals.paycheckCoverageRatio).toBeNull();
     expect(snapshot.comparisons.highestCategory).toBeNull();
     expect(snapshot.comparisons.largestExpense).toBeNull();
+    expect(snapshot.insight).toBeNull();
   });
 });

src/lib/dashboard.ts

@@ -1,4 +1,4 @@
-import type { Expense, Paycheck } from "@prisma/client";
+import type { Expense, MonthlyInsight, Paycheck } from "@prisma/client";
 
 import { db } from "@/lib/db";
 import {
@@ -12,6 +12,11 @@ import {
 
 export type DashboardSnapshot = {
   month: string;
+  insight: {
+    summary: string;
+    recommendations: string;
+    generatedAt: string;
+  } | null;
   totals: {
     expensesCents: number;
     paychecksCents: number;
@@ -32,6 +37,7 @@ export function buildDashboardSnapshot(input: {
   month: string;
   expenses: Expense[];
   paychecks: Paycheck[];
+  insight?: MonthlyInsight | null;
 }): DashboardSnapshot {
   const monthExpenses = input.expenses.filter((expense) => isDateInMonth(expense.date, input.month));
   const monthPaychecks = input.paychecks.filter((paycheck) => isDateInMonth(paycheck.payDate, input.month));
@@ -80,6 +86,13 @@ export function buildDashboardSnapshot(input: {
 
   return {
     month: input.month,
+    insight: input.insight
+      ? {
+          summary: input.insight.summary,
+          recommendations: input.insight.recommendations,
+          generatedAt: input.insight.generatedAt.toISOString(),
+        }
+      : null,
     totals: {
       expensesCents,
       paychecksCents,
@@ -115,10 +128,11 @@ export function buildDashboardSnapshot(input: {
 }
 
 export async function getDashboardSnapshot(month = getCurrentMonthKey()) {
-  const [expenses, paychecks] = await Promise.all([
+  const [expenses, paychecks, insight] = await Promise.all([
     db.expense.findMany({ orderBy: [{ date: "desc" }, { createdAt: "desc" }] }),
     db.paycheck.findMany({ orderBy: [{ payDate: "desc" }, { createdAt: "desc" }] }),
+    db.monthlyInsight.findUnique({ where: { month } }),
   ]);
 
-  return buildDashboardSnapshot({ month, expenses, paychecks });
+  return buildDashboardSnapshot({ month, expenses, paychecks, insight });
 }

src/lib/insights.test.ts

@@ -0,0 +1,91 @@
+import { afterEach, describe, expect, it, vi } from "vitest";
+
+vi.mock("@/lib/db", () => {
+  const monthlyInsight = {
+    upsert: vi.fn(async ({ where, update, create }: { where: { month: string }; update: Record<string, unknown>; create: Record<string, unknown> }) => ({
+      id: "insight-1",
+      month: where.month,
+      year: (update.year ?? create.year) as number,
+      summary: (update.summary ?? create.summary) as string,
+      recommendations: (update.recommendations ?? create.recommendations) as string,
+      inputSnapshot: (update.inputSnapshot ?? create.inputSnapshot) as string,
+      generatedAt: new Date("2026-03-23T12:00:00.000Z"),
+    })),
+    findUnique: vi.fn(),
+  };
+
+  return {
+    db: {
+      expense: { findMany: vi.fn() },
+      paycheck: { findMany: vi.fn() },
+      monthlyInsight,
+    },
+  };
+});
+
+describe("generateMonthlyInsight", () => {
+  afterEach(() => {
+    vi.restoreAllMocks();
+  });
+
+  it("stores a fallback for sparse months", async () => {
+    const { db } = await import("@/lib/db");
+    const { generateMonthlyInsight } = await import("@/lib/insights");
+
+    vi.mocked(db.expense.findMany).mockResolvedValue([]);
+    vi.mocked(db.paycheck.findMany).mockResolvedValue([]);
+
+    const result = await generateMonthlyInsight("2026-03");
+
+    expect(result.source).toBe("fallback");
+    expect(result.insight.summary).toContain("not enough activity");
+  });
+
+  it("stores model output when Ollama responds", async () => {
+    const { db } = await import("@/lib/db");
+    const { generateMonthlyInsight } = await import("@/lib/insights");
+
+    vi.mocked(db.expense.findMany).mockResolvedValue([
+      {
+        id: "expense-1",
+        title: "Groceries",
+        date: "2026-03-23",
+        amountCents: 3200,
+        category: "FOOD",
+        createdAt: new Date("2026-03-23T10:00:00.000Z"),
+      },
+      {
+        id: "expense-2",
+        title: "Rent",
+        date: "2026-03-02",
+        amountCents: 120000,
+        category: "RENT",
+        createdAt: new Date("2026-03-02T10:00:00.000Z"),
+      },
+    ]);
+    vi.mocked(db.paycheck.findMany).mockResolvedValue([
+      {
+        id: "paycheck-1",
+        payDate: "2026-03-01",
+        amountCents: 180000,
+        createdAt: new Date("2026-03-01T10:00:00.000Z"),
+      },
+    ]);
+
+    vi.spyOn(globalThis, "fetch").mockResolvedValue({
+      ok: true,
+      json: async () => ({
+        response: JSON.stringify({
+          summary: "Spending is stable.",
+          recommendations: "Keep food spending under watch.",
+        }),
+      }),
+    } as Response);
+
+    const result = await generateMonthlyInsight("2026-03");
+
+    expect(result.source).toBe("model");
+    expect(result.insight.summary).toBe("Spending is stable.");
+    expect(result.insight.recommendations).toBe("Keep food spending under watch.");
+  });
+});

src/lib/insights.ts

@@ -0,0 +1,149 @@
+import type { MonthlyInsight } from "@prisma/client";
+
+import { db } from "@/lib/db";
+import { getCurrentMonthKey } from "@/lib/date";
+import { getDashboardSnapshot } from "@/lib/dashboard";
+import { generateOllamaJson, OllamaUnavailableError } from "@/lib/ollama";
+
+export type InsightResult = {
+  insight: MonthlyInsight;
+  source: "model" | "fallback";
+};
+
+type GeneratedInsightPayload = {
+  summary?: string;
+  recommendations?: string;
+};
+
+function coerceInsightText(value: unknown) {
+  if (typeof value === "string") {
+    return value.trim();
+  }
+
+  if (Array.isArray(value)) {
+    return value
+      .map((item) => (typeof item === "string" ? item.trim() : ""))
+      .filter(Boolean)
+      .join(" ")
+      .trim();
+  }
+
+  if (value && typeof value === "object") {
+    return Object.values(value)
+      .map((item) => (typeof item === "string" ? item.trim() : ""))
+      .filter(Boolean)
+      .join(" ")
+      .trim();
+  }
+
+  return "";
+}
+
+function buildFallbackInsight(month: string, reason: "sparse" | "unavailable") {
+  if (reason === "unavailable") {
+    return {
+      summary: `Local insights are unavailable for ${month} because Ollama or the selected model is not reachable right now.`,
+      recommendations:
+        "Keep tracking manually for now. Once Ollama is running again, regenerate this month to get a private offline summary.",
+    };
+  }
+
+  return {
+    summary: `There is not enough activity in ${month} yet to generate a useful insight summary.`,
+    recommendations:
+      "Add more expenses or paychecks this month, then generate insights again for stronger spending and timing guidance.",
+  };
+}
+
+function buildInsightPrompt(snapshot: Awaited<ReturnType<typeof getDashboardSnapshot>>) {
+  return [
+    "You are a private offline financial summarizer for a single-user expense tracker.",
+    "Return strict JSON with keys summary and recommendations.",
+    "Keep the tone practical, concise, and non-judgmental.",
+    "Focus on spending patterns, category spikes, paycheck timing, and next-month guidance.",
+    `Month: ${snapshot.month}`,
+    `Total expenses cents: ${snapshot.totals.expensesCents}`,
+    `Total paychecks cents: ${snapshot.totals.paychecksCents}`,
+    `Net cash flow cents: ${snapshot.totals.netCashFlowCents}`,
+    `Average daily spend cents: ${snapshot.totals.averageDailySpendCents}`,
+    `Highest category: ${snapshot.comparisons.highestCategory ? `${snapshot.comparisons.highestCategory.category} ${snapshot.comparisons.highestCategory.amountCents}` : "none"}`,
+    `Largest expense: ${snapshot.comparisons.largestExpense ? `${snapshot.comparisons.largestExpense.title} ${snapshot.comparisons.largestExpense.amountCents}` : "none"}`,
+    `Category breakdown: ${JSON.stringify(snapshot.categoryBreakdown)}`,
+    `Recent expenses: ${JSON.stringify(snapshot.recentExpenses)}`,
+    `Daily chart points: ${JSON.stringify(snapshot.chart)}`,
+  ].join("\n");
+}
+
+async function upsertMonthlyInsight(month: string, payload: { summary: string; recommendations: string; inputSnapshot: string }) {
+  const year = Number.parseInt(month.slice(0, 4), 10);
+
+  return db.monthlyInsight.upsert({
+    where: { month },
+    update: {
+      year,
+      summary: payload.summary,
+      recommendations: payload.recommendations,
+      inputSnapshot: payload.inputSnapshot,
+      generatedAt: new Date(),
+    },
+    create: {
+      month,
+      year,
+      summary: payload.summary,
+      recommendations: payload.recommendations,
+      inputSnapshot: payload.inputSnapshot,
+    },
+  });
+}
+
+export async function getStoredMonthlyInsight(month = getCurrentMonthKey()) {
+  return db.monthlyInsight.findUnique({ where: { month } });
+}
+
+export async function generateMonthlyInsight(month = getCurrentMonthKey()): Promise<InsightResult> {
+  const snapshot = await getDashboardSnapshot(month);
+  const totalEvents = snapshot.recentExpenses.length + snapshot.chart.filter((point) => point.paychecksCents > 0).length;
+
+  if (totalEvents < 2) {
+    const fallback = buildFallbackInsight(month, "sparse");
+    const insight = await upsertMonthlyInsight(month, {
+      ...fallback,
+      inputSnapshot: JSON.stringify(snapshot),
+    });
+
+    return { insight, source: "fallback" };
+  }
+
+  try {
+    const generated = await generateOllamaJson<GeneratedInsightPayload>({
+      prompt: buildInsightPrompt(snapshot),
+    });
+
+    const summary = coerceInsightText(generated.summary);
+    const recommendations = coerceInsightText(generated.recommendations);
+
+    if (!summary || !recommendations) {
+      throw new OllamaUnavailableError("The local model returned an incomplete insight response.");
+    }
+
+    const insight = await upsertMonthlyInsight(month, {
+      summary,
+      recommendations,
+      inputSnapshot: JSON.stringify(snapshot),
+    });
+
+    return { insight, source: "model" };
+  } catch (error) {
+    if (!(error instanceof OllamaUnavailableError)) {
+      throw error;
+    }
+
+    const fallback = buildFallbackInsight(month, "unavailable");
+    const insight = await upsertMonthlyInsight(month, {
+      ...fallback,
+      inputSnapshot: JSON.stringify(snapshot),
+    });
+
+    return { insight, source: "fallback" };
+  }
+}

src/lib/ollama.ts

@@ -0,0 +1,46 @@
+export class OllamaUnavailableError extends Error {
+  constructor(message = "Local AI runtime is unavailable.") {
+    super(message);
+    this.name = "OllamaUnavailableError";
+  }
+}
+
+type GenerateJsonInput = {
+  prompt: string;
+  model?: string;
+};
+
+export async function generateOllamaJson<T>({ prompt, model }: GenerateJsonInput): Promise<T> {
+  const baseUrl = (process.env.OLLAMA_URL ?? "http://127.0.0.1:11434").replace(/\/$/, "");
+  const selectedModel = model ?? process.env.OLLAMA_MODEL ?? "qwen3.5:9b";
+
+  let response: Response;
+
+  try {
+    response = await fetch(`${baseUrl}/api/generate`, {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({
+        model: selectedModel,
+        format: "json",
+        stream: false,
+        prompt,
+      }),
+    });
+  } catch {
+    throw new OllamaUnavailableError("Ollama is not reachable at the configured URL.");
+  }
+
+  if (!response.ok) {
+    throw new OllamaUnavailableError(`Ollama request failed with status ${response.status}.`);
+  }
+
+  const payload = (await response.json()) as { response?: string; thinking?: string };
+  const jsonText = payload.response?.trim() ? payload.response : payload.thinking;
+
+  if (!jsonText) {
+    throw new OllamaUnavailableError("Ollama returned an empty response.");
+  }
+
+  return JSON.parse(jsonText) as T;
+}