Add Mastra Next.js Postgres Redis sample

.github/workflows/deploy-changed-samples.yml

@@ -94,6 +94,7 @@ jobs:
           TEST_MONGO_INITDB_ROOT_USERNAME: ${{ secrets.TEST_MONGO_INITDB_ROOT_USERNAME }}
           TEST_MONGO_INITDB_ROOT_PASSWORD: ${{ secrets.TEST_MONGO_INITDB_ROOT_PASSWORD }}
           TEST_LLM_MODEL: ${{ secrets.TEST_LLM_MODEL }}
+          TEST_EMBEDDING_MODEL: ${{ secrets.TEST_EMBEDDING_MODEL }}
           TEST_N8N_ENCRYPTION_KEY: ${{ secrets.TEST_N8N_ENCRYPTION_KEY }}
           TEST_NC_DB: ${{ secrets.TEST_NC_DB }}
           TEST_NC_S3_ENDPOINT: ${{ secrets.TEST_NC_S3_ENDPOINT }}

README.md

@@ -56,6 +56,7 @@ When you add a new sample, make sure to add any config vals to the `deploy-chang
 | [Managed LLM](./samples/managed-llm) | An app using Managed LLMs with Defang's OpenAI Access Gateway. | LLM, OpenAI, Python, Bedrock, Vertex | Python |
 | [Managed LLM with Docker Model Provider](./samples/managed-llm-provider) | An app using Managed LLMs with a Docker Model Provider, deployed with Defang. | LLM, Python, Bedrock, Vertex, Docker Model Provider | Python |
 | [Mastra & Next.js](./samples/mastra-nextjs) | An AI-powered tool for chatting with GitHub repositories using Mastra and Google Gemini. | AI, GitHub, Mastra, Next.js, PostgreSQL, TypeScript | TypeScript, JavaScript, Docker |
+| [Mastra & Next.js & PostgreSQL & Redis](./samples/mastra-nextjs-postgres-redis) | A multi-service Mastra support and ops copilot with background jobs, PostgreSQL, Redis, and managed LLM access. | Mastra, Next.js, PostgreSQL, Redis, BullMQ, AI, Agents, Support, Operations | TypeScript, JavaScript, Docker |
 | [Model Context Protocol (MCP) Chatbot](./samples/mcp) | An MCP (Model Context Protocol) chatbot assistant built with Next.js, Python, and Anthropic Claude. | MCP, Next.js, Python, Quart, Claude, AI, Anthropic, TypeScript, React, JavaScript | nodejs, python |
 | [Metabase & PostgreSQL](./samples/metabase) | A simple Metabase configuration with a PostgreSQL database. | Metabase, PostgreSQL, Analytics, Database | SQL |
 | [n8n](./samples/n8n) | A n8n app running on Defang. | n8n, PostgreSQL, Docker | Docker, Shell |

samples/mastra-extended/.gitignore

@@ -0,0 +1 @@
+node_modules

samples/mastra-extended/README.md

@@ -0,0 +1,98 @@
+# Mastra & Next.js & PostgreSQL & Redis
+
+[![1-click-deploy](https://raw.githubusercontent.com/DefangLabs/defang-assets/main/Logos/Buttons/SVG/deploy-with-defang.svg)](https://portal.defang.dev/redirect?url=https%3A%2F%2Fgithub.com%2Fnew%3Ftemplate_name%3Dsample-mastra-nextjs-postgres-redis-template%26template_owner%3DDefangSamples)
+
+This sample shows a multi-service AI app built with [Mastra](https://mastra.ai/), Next.js, PostgreSQL (with pgvector), Redis, and BullMQ, deployed with Defang from a single Docker Compose file.
+
+A background worker generates sample tasks and events with an LLM, pushes them to a queue, then they get classified and stored with vector embeddings in PostgreSQL for semantic search. A Mastra-powered chat agent uses tools to inspect the current state before answering questions.
+
+## Prerequisites
+
+1. Download [Defang CLI](https://github.com/DefangLabs/defang)
+2. (Optional) If you are using [Defang BYOC](https://docs.defang.io/docs/concepts/defang-byoc) authenticate with your cloud provider account
+3. (Optional for local development) [Docker CLI](https://docs.docker.com/engine/install/)
+
+## Development
+
+To run the application locally for development, use the development compose file:
+
+```bash
+docker compose -f compose.dev.yaml up --build
+```
+
+This will:
+
+- Start the Next.js app on `http://localhost:3000`
+- Start PostgreSQL on port 5432
+- Start Redis on port 6379
+- Start a background worker for item classification
+- Start Docker model-provider services for chat + embeddings
+
+Local development uses:
+
+- `ai/qwen2.5:3B-Q4_K_M` for chat/tool-calling
+- `mxbai-embed-large` for embeddings
+
+This matches the CrewAI sample's local model setup and relies on Docker Model Runner / model-provider support being available in your local Docker installation. The first run will download both models, so startup can take a few minutes.
+If `docker compose -f compose.dev.yaml up` fails with `exec: "model": executable file not found in $PATH`, your local Docker installation does not have Docker Model Runner enabled yet.
+To keep iteration practical on CPU-only setups, `compose.dev.yaml` enables `LOCAL_FAST_DATA=true`, which uses deterministic sample generation and classification locally while still exercising the real chat and embedding services.
+
+In deployed environments, the app uses dedicated `chat` and `embedding` model services defined in `compose.yaml`. Defang injects OpenAI-compatible `CHAT_URL` / `CHAT_MODEL` and `EMBEDDING_URL` / `EMBEDDING_MODEL` environment variables automatically, so the application code stays platform-independent.
+
+## Configuration
+
+For this sample, you will need to provide the following [configuration](https://docs.defang.io/docs/concepts/configuration). Note that if you are using the 1-click deploy option, you can set these values as secrets in your GitHub repository and the action will automatically deploy them for you.
+
+### `POSTGRES_PASSWORD`
+
+The password for your PostgreSQL database. You need to set this before deploying for the first time.
+
+*You can easily set this to a random string using `defang config set POSTGRES_PASSWORD --random`*
+
+## Usage
+
+1. Open the app.
+2. Click **Generate sample items**.
+3. Watch the worker create 10 tasks and 10 events, then fan out per-item classify/embed jobs (progress updates in real time via SSE).
+4. Ask questions like:
+   - `What should I look at first?`
+   - `Summarize the tasks and events.`
+   - `Which items seem related?`
+   - `Find events similar to the deploy rollback.`
+
+## Deployment
+
+> [!NOTE]
+> Download [Defang CLI](https://github.com/DefangLabs/defang)
+
+### Defang Playground
+
+Deploy your application to the Defang Playground by opening up your terminal and typing:
+
+```bash
+defang compose up
+```
+
+### BYOC (Deploy to your own AWS or GCP cloud account)
+
+If you want to deploy to your own cloud account, you can [use Defang BYOC](https://docs.defang.io/docs/tutorials/deploy-to-your-cloud).
+
+The default sample uses Defang's managed model provider services:
+
+- `chat` uses `chat-default`
+- `embedding` uses `embedding-default`
+
+If you want to pin different models, edit the `provider.options.model` values in [compose.yaml](/workspaces/defang-global/projects/samples/samples/mastra-nextjs-postgres-redis/compose.yaml).
+
+> [!WARNING]
+> **Extended deployment time:** This sample creates a managed PostgreSQL database which may take upwards of 20 minutes to provision on first deployment. Subsequent deployments are much faster (2-5 minutes).
+
+---
+
+Title: Mastra & Next.js & PostgreSQL & Redis
+
+Short Description: A small Defang sample where background jobs classify and embed tasks and events, and a Mastra copilot answers questions with tools.
+
+Tags: Mastra, Next.js, PostgreSQL, Redis, BullMQ, AI, Agents
+
+Languages: TypeScript, JavaScript, Docker

samples/mastra-extended/app/.dockerignore

@@ -0,0 +1,3 @@
+node_modules
+.next
+npm-debug.log

samples/mastra-extended/app/.gitignore

@@ -0,0 +1,2 @@
+node_modules
+.next

samples/mastra-extended/app/Dockerfile

@@ -0,0 +1,20 @@
+FROM node:22-bookworm-slim
+
+RUN apt-get update -qq \
+    && apt-get install -y curl \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+COPY package*.json ./
+
+RUN npm ci
+
+COPY . .
+
+RUN npm run build
+
+EXPOSE 3000
+
+CMD ["npm", "start"]

samples/mastra-extended/app/next-env.d.ts

@@ -0,0 +1,6 @@
+/// <reference types="next" />
+/// <reference types="next/image-types/global" />
+import "./.next/types/routes.d.ts";
+
+// NOTE: This file should not be edited
+// see https://nextjs.org/docs/app/api-reference/config/typescript for more information.

samples/mastra-extended/app/next.config.ts

@@ -0,0 +1,5 @@
+import type { NextConfig } from "next";
+
+const nextConfig: NextConfig = {};
+
+export default nextConfig;