Add Ollama status checks and Docker deployment

.dockerignore

@@ -0,0 +1,9 @@
+.git
+.next
+node_modules
+npm-debug.log
+.env
+.env.local
+prisma/dev.db
+prisma/dev.db-journal
+coverage

Dockerfile

@@ -0,0 +1,20 @@
+FROM node:22-bookworm-slim AS builder
+WORKDIR /app
+
+COPY package*.json ./
+COPY prisma ./prisma
+RUN npm ci
+
+COPY . .
+RUN npm run prisma:generate && npm run build
+
+FROM node:22-bookworm-slim AS runner
+WORKDIR /app
+ENV NODE_ENV=production
+ENV PORT=3000
+
+COPY --from=builder /app /app
+
+EXPOSE 3000
+
+CMD ["sh", "-c", "npx prisma migrate deploy && npm run start -- --hostname 0.0.0.0"]

README.md

@@ -0,0 +1,51 @@
+# Monthy Tracker
+
+Private monthly expense tracking with local-first storage, offline category suggestions, and offline monthly insights via `Ollama`.
+
+## Local app
+
+1. Install dependencies:
+
+```bash
+npm install
+```
+
+2. Create env config from `.env.example` and keep your local runtime settings:
+
+```bash
+cp .env.example .env
+```
+
+3. Apply migrations and start the app:
+
+```bash
+npx prisma migrate deploy
+npm run dev
+```
+
+4. Keep `Ollama` running with the configured model:
+
+```bash
+ollama serve
+ollama pull qwen3.5:9b
+```
+
+## Docker Compose
+
+Start both the app and `Ollama` together:
+
+```bash
+docker compose up --build
+```
+
+This compose stack will:
+- start `Ollama`
+- pull `qwen3.5:9b` through the `ollama-init` service
+- start the Next.js app on `http://localhost:3000`
+- persist the SQLite database and pulled model with named Docker volumes
+
+## Environment
+
+- `DATABASE_URL` - Prisma SQLite connection string
+- `OLLAMA_URL` - local or container Ollama base URL
+- `OLLAMA_MODEL` - selected model tag, default `qwen3.5:9b`

docker-compose.yml

@@ -0,0 +1,50 @@
+services:
+  ollama:
+    image: ollama/ollama:latest
+    container_name: monthytracker-ollama
+    ports:
+      - "11434:11434"
+    volumes:
+      - ollama_data:/root/.ollama
+    healthcheck:
+      test: ["CMD", "ollama", "list"]
+      interval: 15s
+      timeout: 10s
+      retries: 20
+      start_period: 20s
+
+  ollama-init:
+    image: ollama/ollama:latest
+    depends_on:
+      ollama:
+        condition: service_healthy
+    environment:
+      OLLAMA_HOST: http://ollama:11434
+      OLLAMA_MODEL: ${OLLAMA_MODEL:-qwen3.5:9b}
+    entrypoint: ["/bin/sh", "-c"]
+    command: "ollama pull ${OLLAMA_MODEL:-qwen3.5:9b}"
+    volumes:
+      - ollama_data:/root/.ollama
+    restart: "no"
+
+  app:
+    build:
+      context: .
+    container_name: monthytracker-app
+    depends_on:
+      ollama:
+        condition: service_healthy
+      ollama-init:
+        condition: service_completed_successfully
+    environment:
+      DATABASE_URL: file:/data/dev.db
+      OLLAMA_URL: http://ollama:11434/
+      OLLAMA_MODEL: ${OLLAMA_MODEL:-qwen3.5:9b}
+    ports:
+      - "3000:3000"
+    volumes:
+      - app_data:/data
+
+volumes:
+  ollama_data:
+  app_data:

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

@@ -1,7 +1,7 @@
 ## 1. Project setup
 
 - [x] 1.1 Scaffold the `Next.js` app with TypeScript, linting, and baseline project configuration.
-- [x] 1.2 Add runtime dependencies for Prisma, SQLite, validation, charts, and `OpenAI` integration.
+- [x] 1.2 Add runtime dependencies for Prisma, SQLite, validation, charts, and offline AI integration.
 - [x] 1.3 Add development dependencies and scripts for testing, Prisma generation, and local development.
 - [x] 1.4 Add base environment and ignore-file setup for local database and API key configuration.
 
@@ -34,5 +34,5 @@
 
 ## 6. Verification
 
-- [ ] 6.1 Add automated tests for validation, persistence, dashboard aggregates, offline insight fallback behavior, and category suggestion rules.
+- [x] 6.1 Add automated tests for validation, persistence, dashboard aggregates, offline insight fallback behavior, and category suggestion rules.
 - [x] 6.2 Verify the primary user flows in the browser, including expense entry, paycheck entry, dashboard updates, category suggestion, and insight generation.

src/app/ollama/status/route.ts

@@ -0,0 +1,8 @@
+import { NextResponse } from "next/server";
+
+import { getOllamaStatus } from "@/lib/ollama";
+
+export async function GET() {
+  const status = await getOllamaStatus();
+  return NextResponse.json(status);
+}

src/components/home-dashboard.tsx

@@ -30,11 +30,21 @@ type DashboardSnapshot = {
   chart: Array<{ date: string; expensesCents: number; paychecksCents: number }>;
 };
 
+type OllamaStatus = {
+  available: boolean;
+  configuredModel: string;
+  configuredUrl: string;
+  installedModels: string[];
+  modelReady: boolean;
+  message: string;
+};
+
 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);
+  const [ollamaStatus, setOllamaStatus] = useState<OllamaStatus | null>(null);
 
   async function loadDashboard(month: string) {
     const response = await fetch(`/dashboard?month=${month}`, { cache: "no-store" });
@@ -57,6 +67,16 @@ export function HomeDashboard() {
     return () => window.clearTimeout(timeoutId);
   }, [selectedMonth]);
 
+  useEffect(() => {
+    const timeoutId = window.setTimeout(async () => {
+      const response = await fetch("/ollama/status", { cache: "no-store" });
+      const payload = (await response.json()) as OllamaStatus;
+      setOllamaStatus(payload);
+    }, 0);
+
+    return () => window.clearTimeout(timeoutId);
+  }, []);
+
   const topCategoryLabel = useMemo(() => {
     if (!snapshot?.comparisons.highestCategory) {
       return "No category leader yet";
@@ -161,6 +181,38 @@ export function HomeDashboard() {
           </button>
         </div>
 
+        <div className="mt-6 rounded-3xl border border-stone-200 bg-stone-50 px-5 py-4">
+          <div className="flex flex-wrap items-center justify-between gap-3">
+            <div>
+              <p className="text-xs uppercase tracking-[0.2em] text-stone-500">Ollama runtime</p>
+              <p className="mt-2 text-sm font-medium text-stone-700">
+                {ollamaStatus?.message ?? "Checking local runtime status..."}
+              </p>
+            </div>
+            <div className="rounded-full px-3 py-2 text-xs font-semibold uppercase tracking-[0.2em] text-white "
+              data-ready={ollamaStatus?.available && ollamaStatus?.modelReady ? "true" : "false"}
+            >
+              <span
+                className={
+                  ollamaStatus?.available && ollamaStatus?.modelReady
+                    ? "rounded-full bg-emerald-600 px-3 py-2"
+                    : "rounded-full bg-stone-500 px-3 py-2"
+                }
+              >
+                {ollamaStatus?.available && ollamaStatus?.modelReady ? "Ready" : "Needs attention"}
+              </span>
+            </div>
+          </div>
+          <div className="mt-4 grid gap-3 text-sm text-stone-600 sm:grid-cols-2">
+            <p>
+              Model: <span className="font-semibold text-stone-900">{ollamaStatus?.configuredModel ?? "-"}</span>
+            </p>
+            <p>
+              URL: <span className="font-semibold text-stone-900">{ollamaStatus?.configuredUrl ?? "-"}</span>
+            </p>
+          </div>
+        </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">

src/lib/insights.test.ts

@@ -88,4 +88,51 @@ describe("generateMonthlyInsight", () => {
     expect(result.insight.summary).toBe("Spending is stable.");
     expect(result.insight.recommendations).toBe("Keep food spending under watch.");
   });
+
+  it("coerces array recommendations from the local model", 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 remains manageable.",
+          recommendations: ["Keep groceries planned.", "Move surplus to savings."],
+        }),
+      }),
+    } as Response);
+
+    const result = await generateMonthlyInsight("2026-03");
+
+    expect(result.insight.recommendations).toContain("Keep groceries planned.");
+    expect(result.insight.recommendations).toContain("Move surplus to savings.");
+  });
 });

src/lib/insights.ts

@@ -59,8 +59,10 @@ function buildInsightPrompt(snapshot: Awaited<ReturnType<typeof getDashboardSnap
   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.",
+    "The summary must be a single compact paragraph of at most 3 sentences.",
+    "The recommendations field should be an array with 2 or 3 short action items.",
+    "Keep the tone practical, concise, specific, and non-judgmental.",
+    "Focus on spending patterns, category spikes, paycheck timing, and realistic next-month guidance.",
     `Month: ${snapshot.month}`,
     `Total expenses cents: ${snapshot.totals.expensesCents}`,
     `Total paychecks cents: ${snapshot.totals.paychecksCents}`,
@@ -71,6 +73,7 @@ function buildInsightPrompt(snapshot: Awaited<ReturnType<typeof getDashboardSnap
     `Category breakdown: ${JSON.stringify(snapshot.categoryBreakdown)}`,
     `Recent expenses: ${JSON.stringify(snapshot.recentExpenses)}`,
     `Daily chart points: ${JSON.stringify(snapshot.chart)}`,
+    "Do not mention missing data unless it materially affects the advice.",
   ].join("\n");
 }
 

src/lib/ollama.test.ts

@@ -0,0 +1,38 @@
+import { afterEach, describe, expect, it, vi } from "vitest";
+
+import { generateOllamaJson, getOllamaStatus } from "@/lib/ollama";
+
+describe("getOllamaStatus", () => {
+  afterEach(() => {
+    vi.restoreAllMocks();
+  });
+
+  it("reports model readiness when the configured model is installed", async () => {
+    vi.spyOn(globalThis, "fetch").mockResolvedValue({
+      ok: true,
+      json: async () => ({ models: [{ name: "qwen3.5:9b" }] }),
+    } as Response);
+
+    const status = await getOllamaStatus();
+
+    expect(status.available).toBe(true);
+    expect(status.modelReady).toBe(true);
+  });
+});
+
+describe("generateOllamaJson", () => {
+  afterEach(() => {
+    vi.restoreAllMocks();
+  });
+
+  it("parses json from the thinking field when response is empty", async () => {
+    vi.spyOn(globalThis, "fetch").mockResolvedValue({
+      ok: true,
+      json: async () => ({ response: "", thinking: '{"summary":"ok","recommendations":"ok"}' }),
+    } as Response);
+
+    const result = await generateOllamaJson<{ summary: string; recommendations: string }>({ prompt: "test" });
+
+    expect(result.summary).toBe("ok");
+  });
+});

src/lib/ollama.ts

@@ -5,14 +5,75 @@ export class OllamaUnavailableError extends Error {
   }
 }
 
+export type OllamaStatus = {
+  available: boolean;
+  configuredModel: string;
+  configuredUrl: string;
+  installedModels: string[];
+  modelReady: boolean;
+  message: string;
+};
+
 type GenerateJsonInput = {
   prompt: string;
   model?: string;
 };
 
+function getOllamaConfig() {
+  return {
+    baseUrl: (process.env.OLLAMA_URL ?? "http://127.0.0.1:11434").replace(/\/$/, ""),
+    model: process.env.OLLAMA_MODEL ?? "qwen3.5:9b",
+  };
+}
+
+export async function getOllamaStatus(): Promise<OllamaStatus> {
+  const { baseUrl, model } = getOllamaConfig();
+
+  try {
+    const response = await fetch(`${baseUrl}/api/tags`, {
+      method: "GET",
+      headers: { "Content-Type": "application/json" },
+      cache: "no-store",
+    });
+
+    if (!response.ok) {
+      throw new OllamaUnavailableError(`Ollama status request failed with status ${response.status}.`);
+    }
+
+    const payload = (await response.json()) as { models?: Array<{ name?: string }> };
+    const installedModels = (payload.models ?? []).map((entry) => entry.name).filter((name): name is string => Boolean(name));
+    const modelReady = installedModels.includes(model);
+
+    return {
+      available: true,
+      configuredModel: model,
+      configuredUrl: baseUrl,
+      installedModels,
+      modelReady,
+      message: modelReady
+        ? `Ollama is reachable and ${model} is ready.`
+        : `Ollama is reachable, but ${model} is not pulled yet.`,
+    };
+  } catch (error) {
+    const message =
+      error instanceof OllamaUnavailableError
+        ? error.message
+        : "Ollama is not reachable at the configured URL.";
+
+    return {
+      available: false,
+      configuredModel: model,
+      configuredUrl: baseUrl,
+      installedModels: [],
+      modelReady: false,
+      message,
+    };
+  }
+}
+
 export async function generateOllamaJson<T>({ prompt, model }: GenerateJsonInput): Promise<T> {
-  const baseUrl = (process.env.OLLAMA_URL ?? "http://127.0.0.1:11434").replace(/\/$/, "");
-  const selectedModel = model ?? process.env.OLLAMA_MODEL ?? "qwen3.5:9b";
+  const { baseUrl, model: configuredModel } = getOllamaConfig();
+  const selectedModel = model ?? configuredModel;
 
   let response: Response;