Initial commit

.claude/commands/api.md

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+Scaffold a new API endpoint. Read apps/backend/fastapi/server.py (or flask if BACKEND_MODE=flask) first.
+
+From the arguments, determine:
+- HTTP method and path (e.g. POST /items)
+- Request/response shape
+- Any DB or external service calls needed
+
+Add the route to the appropriate server.py. Follow the existing structure:
+- Use Pydantic models for FastAPI request/response schemas
+- Use dotenv for any config
+- Add proper status codes and error responses
+- Keep business logic out of the route handler; extract to a helper if more than ~15 lines
+
+If a new dependency is needed, add it to requirements.txt.

.claude/commands/build.md

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+Read CLAUDE.md and AGENTS.md. Read the relevant existing code before making any changes.
+
+Implement the feature or task described in the arguments end-to-end across the full stack as needed. Follow the code style rules in CLAUDE.md strictly:
+- No redundant comments, no boilerplate, no fluff
+- Pure functions preferred, side effects at boundaries
+- Reuse what already exists in alveslib before writing new utilities
+- Type all public interfaces
+- Keep modules under 400 lines
+
+After implementing, run a quick sanity check:
+- If Python changed: check imports resolve correctly
+- If Next.js changed: check TypeScript compiles (bun run typecheck)
+- If docker-compose changed: verify YAML is valid
+
+Do not create documentation files. Do not add emojis. Summarize what was done in one paragraph.

.claude/commands/page.md

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+Scaffold a new Next.js App Router page. Read apps/webapp/src/app/layout.tsx and an existing page (e.g. apps/webapp/src/app/page.tsx) for context.
+
+From the arguments, determine:
+- Route path (maps to directory under apps/webapp/src/app/)
+- Whether it needs auth (server component checking Supabase session)
+- Whether it needs client interactivity (use client directive)
+- Data it needs to fetch
+
+Create the page file bare-bones with correct structure - no inline styles. Add any new strings to apps/webapp/src/locales/en/common.json. If a reusable component is needed, create it in apps/webapp/src/components/ without styling (styling is done last per CLAUDE.md).
+
+If the page requires server actions, create an adjacent actions.ts file.

.claude/commands/plan.md

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+Read CLAUDE.md and AGENTS.md to understand the project structure, then read the current state of the codebase.
+
+Given the idea or feature described by the user (provided as arguments to this command, or ask if not given), produce a direct implementation plan:
+
+1. Which parts of the scaffold to use (webapp, backend, worker, ml, src)
+2. What files to create or modify and in what order
+3. What dependencies to add to requirements.txt or package.json
+4. Any services to enable in docker-compose.yml
+5. Any env vars to add to .env.example
+
+Be specific and concrete. No fluff. The plan should be immediately actionable by you or a developer.

.claude/commands/review.md

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+Run `git diff HEAD` (or `git diff HEAD~1` if nothing staged) to get recent changes.
+
+Review the diff for:
+1. Correctness - logic errors, off-by-ones, missing error handling
+2. Code style - violations of CLAUDE.md tenets (redundancy, unclear names, noisy loops)
+3. Security - exposed secrets, unvalidated input, CORS issues, SQL injection surface
+4. Performance - N+1 queries, blocking I/O in async context, missing indices
+5. Missing edge cases or TODOs that should be addressed before shipping
+
+Be direct. List issues with file:line references where possible. Skip praise.

.claude/commands/ship.md

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+Stage all meaningful changes and create a commit with a concise, accurate message following conventional commits format (feat:, fix:, refactor:, chore:, etc.).
+
+Steps:
+1. Run `git status` and `git diff` to understand what changed
+2. Skip any generated files, lockfiles (unless intentional), secrets, or build artifacts
+3. Stage the relevant changes with `git add`
+4. Write a commit message: one-line summary (type: description), optional body if needed
+5. Commit
+
+Do not push unless explicitly asked. Do not amend existing commits. Report what was committed.

.dockerignore

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+# Version control
+.git
+.gitignore
+
+# Node / frontend
+**/node_modules
+apps/webapp/.next
+apps/webapp/bun.lock
+
+# Python
+**/__pycache__
+**/*.pyc
+**/*.pyo
+.venv
+**/.venv
+*.egg-info
+build/
+dist/
+
+# Dev artifacts
+.env
+**/.env
+**/.scraper_cache
+**/downloaded_files
+logs/
+ml/tensorboard/
+ml/notebooks/
+FLAT.xml
+
+# Docs / meta
+*.md
+AGENTS.md
+CLAUDE.md
+.github/

.env.example

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+NAME=myproject
+COMPOSE_PROJECT_NAME=$NAME
+
+# Backend
+BACKEND_MODE=fastapi
+BACKEND_PORT=9812
+
+# Ports
+REDIS_PORT=6378
+GRAFANA_PORT=3125
+LOKI_PORT=3142
+
+# PostgreSQL
+POSTGRES_PORT=5432
+POSTGRES_DB=app
+POSTGRES_USER=postgres
+POSTGRES_PASSWORD=postgres
+POSTGRES_HOST=localhost
+
+# MongoDB
+MONGO_PORT=27017
+MONGO_DB=app
+MONGO_USER=admin
+MONGO_PASSWORD=admin123
+MONGO_HOST=localhost
+
+DATABASE_TYPE=postgres
+
+# Redis
+REDIS_URL=redis://localhost:$REDIS_PORT
+
+# Logging
+LOGDIR="/tmp/logs-$NAME/"
+
+# Supabase (webapp auth - set NEXT_PUBLIC_REQUIRE_AUTH=true to enable gating)
+NEXT_PUBLIC_REQUIRE_AUTH=false
+NEXT_PUBLIC_SUPABASE_URL=https://your-project.supabase.co
+NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY=your_supabase_anon_key_here
+
+# MinIO
+MINIO_ROOT_USER=minioadmin
+MINIO_ROOT_PASSWORD=minioadmin
+MINIO_ENDPOINT=localhost:9900
+
+# ML
+ML_LATEST_WEIGHTS_PATH=/app/models/weights
+MLFLOW_TRACKING_URI=http://localhost:5000
+
+# AI / Agents
+ANTHROPIC_API_KEY=sk-ant-...
+# Optional: use Bedrock instead of direct Anthropic API
+# CLAUDE_CODE_USE_BEDROCK=1
+# Optional: use Vertex AI
+# CLAUDE_CODE_USE_VERTEX=1

.github/workflows/ci.yml

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+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  webapp:
+    name: Next.js build
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: oven-sh/setup-bun@v2
+        with:
+          bun-version: latest
+      - name: Install dependencies
+        working-directory: apps/webapp
+        run: bun install --frozen-lockfile
+      - name: Type check
+        working-directory: apps/webapp
+        run: bun run typecheck
+      - name: Build
+        working-directory: apps/webapp
+        run: bun run build
+        env:
+          NEXT_PUBLIC_REQUIRE_AUTH: "false"
+          NEXT_PUBLIC_SUPABASE_URL: "https://placeholder.supabase.co"
+          NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY: "placeholder"
+
+  python:
+    name: Python lint + import check
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+      - name: Install deps
+        run: pip install ruff python-dotenv
+      - name: Lint
+        run: ruff check src/ ml/ apps/worker/ apps/backend/ alveslib/ || true
+      - name: Import smoke test
+        run: |
+          python -c "from alveslib.logger import get_logger; print('logger ok')"
+          python -c "from alveslib.scraper import ScraperCache; print('scraper ok')" || true

.gitignore

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+**/node_modules
+*.env
+.venv/
+**/__pycache__
+**/.scraper_cache/
+**/downloaded_files/
+**.egg-info/
+logs/
+FLAT.xml
+**/package-lock.json
+.nx/

AGENTS.md

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+# UltiPlate - Agent Instructions
+
+Scaffold for any project: webapp, API, ML pipeline, scraper, worker, CLI, or SDK. Deployable via Makefile and Docker Compose.
+
+## Project Layout
+
+```
+apps/webapp/          Next.js 15 + React 19 + Tailwind 4 (Bun, Turbopack, auth optional)
+apps/webapp-minimal/  Streamlit prototype
+apps/backend/fastapi/ FastAPI server
+apps/backend/flask/   Flask server
+apps/worker/          Celery worker (Redis broker)
+ml/                   PyTorch ML pipeline (arch, train, inference, etl)
+alveslib/             Shared Python library: logger, scraper, agent
+src/                  Simple scripts / CLI
+```
+
+## Rules for Agents
+
+- Use `make init` to bootstrap. Use `make dev` to run webapp. Use `make help` for all targets.
+- Python deps: use root `pyproject.toml` + `uv.lock`; `make envlink` propagates `.env` to sub-apps.
+- JS/TS: Bun is the package manager for `apps/webapp`. Use `bun add` / `bun install` / `bun dev`.
+- Do not create rogue files or test scripts outside the established structure.
+- All shared Python utilities go in `alveslib/`. Import from there, never duplicate logic.
+- No emojis in code, comments, or logs.
+
+## AI / Agent SDK
+
+`ANTHROPIC_API_KEY` is required for AI features. `alveslib.agent` provides:
+
+```python
+from alveslib import ask, stream, Agent
+
+ask("prompt")            # blocking one-shot
+stream("prompt")         # iterator of text chunks
+Agent(system="...").chat("prompt")  # multi-turn
+```
+
+For full agentic loops with file/bash tools, use the Claude Agent SDK:
+```bash
+pip install claude-agent-sdk
+```
+```python
+from claude_agent_sdk import query, ClaudeAgentOptions
+async for msg in query(prompt="...", options=ClaudeAgentOptions(allowed_tools=["Read","Bash"])):
+    print(msg)
+```
+
+## Slash Commands (.claude/commands/)
+
+Use in Claude Code sessions (type `/`):
+- `/plan` - plan an implementation within this boilerplate
+- `/build` - implement a feature end-to-end
+- `/api` - scaffold a backend endpoint
+- `/page` - scaffold a Next.js page
+- `/review` - review recent changes
+- `/ship` - commit staged changes

CLAUDE.md

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+# Template
+My template repository for almost any project that I might be doing in the field of AI or building a software product or any sort of tool ranging form a machine learning project, data analysis, SaaS app or a python library or some sort of API or scraper or ETL tool or some sort of simulation or just a small python program to run something simple.
+This template is AI native and platform agnostic and meant to be effortlessly deployable to anywhere at any time with any software with minimal effort managed via my Makefile.
+
+#### Directory Breakdown
+- apps
+  - webapp (A next.js 15.5.2 webapp with react 19 pre-configured with basics and Tailwind CSS)
+    - This can server both as the frontend but also nextjs allows for API route definitions for simple things that we could build.
+  - webapp-minimal (Streamlit webapp with minimal web interface for quick prototypes)
+  - worker (Background worker template for long running tasks for programs)
+  - backend/{fastapi|flask} to define a web api with either or whichever is specified/user wants or is a best fit scenario.
+- ml (Machine learning pipeline for PyTorch)
+  - models (arch.py where we define architectures and train.py for the training loop)
+  - inference.py (A minimal setup webserver with fastapi to run inference online)
+  - notebooks (For any notebook needs)
+  - data (has etl.py for any ETL and should be a single place for turning raw data into pytorch ready datasets)
+- src (Just as __init__.py for any simple modules or building libraries within there, should be used for simple python scripts without any otehr needs or just running something in the CLI)
+
+
+#### Services Associated
+- I setup a basic optional minio service to run for any needs of object storage or manipulation for any machine learning tasks
+- Tensorboard is very useful for monitoring experiments and is defined as a docker service an spinupable with the make tensorboard command.
+
+###### Logging
+1. Grafana to view (must be configured by adding loki url with "http://loki:31000")
+2. For now just python directly adds the logs to loki (via the alveslib package)
+
+```python
+from alveslib import get_logger
+logger = get_logger("service") # if you are writing contents for logs or any relevant prints do not use emojis in any debug statements or logs.
+```
+FOR REFERENCE ALL OTHER REUSABLE MODULES LIKE THIS SHOULD BE DEFINED THE SAME WAY IN THE ALVESLIB package - if used in python.
+Using lazydocker to manager containers...
+
+### Checklists and Best Practices and Code Hygine
+
+#### `apps/webapp` - building a nextjs app.
+
+Reusability is key - define modules and do not repeat code or logic anywhere. Style should be done LAST, when defining new components define them bare-bones or motivated with globals.css if compelted. You can make use of https://reactbits.dev/
+
+- [ ] Make sure to update layout.tsx with proper title and meta description
+- [ ] Using a provided moodboard -> create a globals.css update to match the style [use creative structure for each project differently (do not take provided as given)]
+- [ ] Flesh out proper content for the TOC and Privacy Policy - write content for both of the components to properly define them
+- [ ] Optionally turn off eslint
+- [ ] Properly stylize the Header and Footer
+- [ ] Define the robots.txt and llms.txt
+- [ ] Connect a supabase project if it is being used and properly spin up a local supabase container setup if desired for local testing. If a webapp does not require user auth (or just yet) just remove references to the /login /dashboard routes but do not delete the code of using them.
+- [ ] Connect analytics with google with `gtag package`
+
+#### `ml/data` - using and building datasets for ML
+Parallel data loading and using third party datasets. All code written must ensure that running the model training is possible on any machine.
+Downloading data from third party sources must be done in a reproducible way (the export part of the ETL). If datasets are too large for just pandas, using spark is the best way forward.
+More on ETL: Dataset ETL: deterministic, resumable, cached stages. Hash raw inputs and params to derive cache keys. If data missing at runtime, trigger acquisition with rate-limited, cached requests.
+Data processing should be cachable so if any stage of the transformation or data processing fails it does not start from scrach. If a dataloader class is being used and data is not present on the system, it should trigger logic to get the data and handle any transformations necssary. The whole pipeline should be self informed about what is hapenning and aware of the phase its in. If third party requests are made ferquently, they should also be cached to prevent overloading any servers.
+Dataloaders defined in pytorch if handling for example 1e6 images with a storage bucket like minio (just a dummy example it should be generaliziable) must stream the data as it is being used for training just in time. (refer streaming (IterableDatasets), WebDataset/tar shards, or torchdata for 1e6+ items. Avoid loading whole corpora in memory.)
+
+#### `ml/models` - creating model architectures and defining training loops
+Define the architectuer in arch.py and training loop in train.py - training should be logged with tensorboard always and evaluations metrics should be versioned and defined in separate logic units like eval.py to make experiments comparable, if at any poitns eval metrics change or scale they should be tracked under a sparate track of experiments in tensorboard - do not arbitrarily modify the eval of anything or loss unless explicitly necessary.
+Experiments should be tracked with meaningful names and logging any parameters into experiments. Machine learning is a life cycle and always evolving. DO NOT create any rogue execution scripts just use the train.py for training.
+## Code style notes
+- Prefer pure functions where possible. Keep side effects at boundaries. Make sure functions or classes you write do not repeat code or logic and are highly modular with minimal code expressions for solutions. Use list/dictionary comprehension to generate cleaner code that is easily readable. Feel free to use shorter and more sucient variable names.
+- when it comes to writing comments if you have a lot to say do not split up comments on multipline by multiple consequent # or // symbols but rather write complete sentences and comment directly next to logic - do not use any emojis in comments and feel free to not use perfect grammar.
+- Keep modules <300–400 lines where possible. Extract helpers early into unified scripts and avoid generating noisy scattered solutions. File structure should extract library and reusable components into alveslib or into locally importable modules. 
+- Type everything at public boundaries. mypy-friendly.
+- Return precise errors. Avoid blanket exceptions. But avoid noisy try-catch multiple nested layers.
+
+## IMPORTANT
+Do NOT externalize or document your work, usage guidelines, or benchmarks (e.g., README.md, CONTRIBUTING.md, SUMMARY.md, USAGE_GUIDELINES.md) after completing the task — unless you are explicitly instructed to do so.
+
+You may include a brief summary of your work, but do not create separate documentation files for it
+
+# Code Confession and Tenets - By CLAUDE for future CLAUDE code instances
+What I did wrong in the past and might be tempted to do
+
+I wrote bloated, amateur garbage that insults the reader's intelligence. The original code had:
+- 40+ lines to do what takes 15 or even 5
+- Comments explaining tokenizer.batch_decode() like you're an idiot 
+- Variable names like cer_scores, wer_scores, ned_scores, hybrid_losses with individual append loops instead of one list comprehension
+- Whitespace between every line like I'm being paid by vertical space
+- Three separate loops iterating over the same data
+- Args/Returns docstrings stating the obvious
+
+The Tenets:
+
+1. Code is read, not performed - Every line should carry weight. Whitespace is not decoration.
+2. One pass, one purpose - If you're looping multiple times over the same data, you failed.
+3. Compression over explanation - pred_ids = np.argmax(preds[0] if isinstance(preds, tuple) else preds,
+  axis=-1) is clearer than five lines with intermediate variables.
+4. Comments are failure - If your code needs comments to be understood, you named things wrong or
+structured it poorly unless deeply technical or niche.
+5. List comprehensions over loops - [compute_ocr_metrics(gt, pred) for gt, pred in zip(label_texts, 
+pred_texts)] beats a for loop with appends.
+6. Return early, return directly - Don't create a variable just to return it on the next line.
+7. Closures over classes - create_compute_metrics returns a closure with tokenizer captured - no need
+for a class with one method.
+8. Trust the reader - They know what eval_pred is. They don't need a docstring.
+
+The code should be dense, efficient, and assume intelligence. Anything else is disrespect.
+Before writing code, understand the problem's physics. OOM means "ran out during operation" not "didn't clean up after." Surface-level pattern matching kills code quality.

Makefile

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+# Makefile - Ultiplate Template
+.PHONY: help init bootstrap venv deps lock envlink fmt lint type test clean doctor
+.PHONY: up down logs ps rebuild
+.PHONY: dev run.webapp run.webapp.simple run.backend run.worker run.ml
+.PHONY: lift lift.minio lift.tensorboard lift.mlflow lift.logging lift.database
+.PHONY: etl train infer seed
+.PHONY: nx.graph nx.projects nx.affected
+.DEFAULT_GOAL := help
+
+WD         := $(shell pwd)
+ENV        := $(shell readlink -f .env 2>/dev/null || echo .env)
+PYTHON_VER := 3.12
+PYTHON     := python$(PYTHON_VER)
+UV         := $(shell command -v uv 2>/dev/null || echo uv)
+BUN        := $(shell command -v bun 2>/dev/null || echo bun)
+NX         := $(BUN) x nx
+
+## ── Quick Start ──────────────────────────────────────────────────────────────
+
+init: bootstrap ## First-time setup (alias for bootstrap)
+
+dev: run.webapp ## Start the Next.js webapp (fastest entry point)
+
+## ── Environment Setup ────────────────────────────────────────────────────────
+
+bootstrap: venv envlink deps ## Full initial setup: venv + deps + env linking
+	@echo "Bootstrap complete. Activate Python env: source .venv/bin/activate"
+
+venv: ## Create Python virtual environment (idempotent)
+	@if [ ! -d ".venv" ]; then \
+		echo "Creating uv-managed venv (Python $(PYTHON_VER))..."; \
+		$(UV) venv --python $(PYTHON_VER) .venv; \
+	fi
+
+deps: venv ## Install/update Python dependencies
+	@$(UV) sync
+	@if [ -f package.json ]; then $(BUN) install; fi
+	@cd apps/webapp && $(BUN) install --frozen-lockfile 2>/dev/null || $(BUN) install
+
+lock: ## Refresh uv lockfile
+	@$(UV) lock
+
+envlink: ## Propagate root .env to all sub-apps
+	@mkdir -p apps/webapp apps/worker ml
+	@touch "$(WD)/apps/webapp/.env" "$(WD)/apps/worker/.env" "$(WD)/ml/.env"
+	@if [ -f "$(ENV)" ]; then \
+		ln -sf "$(ENV)" "$(WD)/apps/webapp/.env"; \
+		ln -sf "$(ENV)" "$(WD)/apps/worker/.env"; \
+		ln -sf "$(ENV)" "$(WD)/ml/.env"; \
+	fi
+
+doctor: ## Verify toolchain (bun, docker, python)
+	@echo "Checking toolchain..."
+	@$(PYTHON) --version || (echo "python$(PYTHON_VER) not found"; exit 1)
+	@$(UV) --version || echo "uv not found - install: curl -LsSf https://astral.sh/uv/install.sh | sh"
+	@$(BUN) --version || echo "bun not found - install: curl -fsSL https://bun.sh/install | bash"
+	@docker --version || echo "docker not found"
+	@docker compose version || echo "docker compose not found"
+	@echo "OK"
+
+## ── Code Quality ─────────────────────────────────────────────────────────────
+
+fmt: venv ## Format Python with black
+	@$(UV) run black src/ ml/ apps/worker/ apps/backend/ 2>/dev/null || echo "Run: make deps"
+
+lint: venv ## Lint Python with ruff
+	@$(UV) run ruff check src/ ml/ apps/worker/ apps/backend/ 2>/dev/null || echo "Run: make deps"
+
+type: venv ## Type check Python with mypy
+	@$(UV) run mypy src/ ml/ apps/worker/ apps/backend/ 2>/dev/null || echo "Run: make deps"
+
+test: venv ## Run pytest
+	@$(UV) run pytest tests/ -v 2>/dev/null || echo "No tests yet - create tests/"
+
+## ── Docker ───────────────────────────────────────────────────────────────────
+
+up: ## Start core services (redis, ml-inference, worker)
+	@docker compose up -d redis ml-inference worker
+
+down: ## Stop all services
+	@docker compose down
+
+logs: ## Tail all service logs
+	@docker compose logs -f
+
+ps: ## Show service status
+	@docker compose ps
+
+rebuild: ## Rebuild + restart all services (no cache)
+	@docker compose build --no-cache && docker compose up -d
+
+## ── Service Profiles ─────────────────────────────────────────────────────────
+
+lift: up ## Alias for 'up'
+
+lift.minio: ## Start core services + MinIO object storage
+	@docker compose --profile minio up -d
+	@echo "MinIO console: http://localhost:9901 (minioadmin/minioadmin)"
+
+lift.tensorboard: ## Start TensorBoard
+	@docker compose --profile tensorboard up -d
+	@echo "TensorBoard: http://localhost:6006"
+
+lift.mlflow: ## Start optional MLflow tracking server
+	@docker compose --profile mlflow up -d
+	@echo "MLflow: http://localhost:5000"
+
+lift.logging: ## Start Loki + Grafana logging stack
+	@docker compose --profile logging up -d
+	@if [ -f .env ]; then . ./.env 2>/dev/null; fi; \
+	echo "Grafana: http://localhost:$${GRAFANA_PORT:-3000} (admin/admin)"; \
+	echo "Loki:    http://localhost:$${LOKI_PORT:-3100}"
+
+lift.database: ## Start database services (postgres/mongodb)
+	@docker compose --profile database up -d
+
+## ── Run Applications ─────────────────────────────────────────────────────────
+
+run.webapp: ## Start Next.js webapp with bun (dev + turbopack)
+	@echo "Starting webapp at http://localhost:3000"
+	@$(NX) run webapp:dev
+
+run.webapp.simple: ## Start Streamlit minimal webapp
+	@$(NX) run webapp-minimal:dev
+
+run.backend: ## Start API backend (BACKEND_MODE=fastapi|flask, default: fastapi)
+	@if [ -f .env ]; then . ./.env; fi; \
+	MODE=$${BACKEND_MODE:-fastapi}; \
+	if [ "$$MODE" = "fastapi" ]; then \
+		$(NX) run backend-fastapi:dev; \
+	elif [ "$$MODE" = "flask" ]; then \
+		$(NX) run backend-flask:dev; \
+	else \
+		echo "Unknown BACKEND_MODE=$$MODE (fastapi|flask)"; exit 1; \
+	fi
+
+run.worker: ## Start Celery worker (requires redis)
+	@$(NX) run worker:dev
+
+run.ml: ## Start ML inference server (FastAPI)
+	@$(NX) run ml:dev
+
+## ── ML Workflow ──────────────────────────────────────────────────────────────
+
+etl: venv ## Run ETL pipeline
+	@$(NX) run ml:etl
+
+train: venv ## Run model training
+	@$(NX) run ml:train
+
+nx.graph: ## Open Nx project graph
+	@$(NX) graph
+
+nx.projects: ## List Nx projects in workspace
+	@$(NX) show projects
+
+nx.affected: ## Run lint/test/build only for affected projects
+	@$(NX) affected -t lint,test,build
+
+infer: run.ml ## Alias for run.ml
+
+## ── Utilities ────────────────────────────────────────────────────────────────
+
+seed: venv ## Seed development data
+	@$(PYTHON) scripts/seed.py 2>/dev/null || echo "Create scripts/seed.py for seeding"
+
+clean: ## Remove caches, build artifacts, and compiled files
+	@find . -type d -name __pycache__ -exec rm -rf {} + 2>/dev/null || true
+	@find . -type f -name "*.pyc" -delete 2>/dev/null || true
+	@find . -type d -name "*.egg-info" -exec rm -rf {} + 2>/dev/null || true
+	@find . -type d -name ".pytest_cache" -exec rm -rf {} + 2>/dev/null || true
+	@find . -type d -name ".mypy_cache" -exec rm -rf {} + 2>/dev/null || true
+	@find . -type d -name ".ruff_cache" -exec rm -rf {} + 2>/dev/null || true
+	@rm -rf build/ dist/ 2>/dev/null || true
+
+help: ## Show this help
+	@echo "Ultiplate - make targets"
+	@echo ""
+	@echo "  Quick start:"
+	@echo "    make init         - First-time setup"
+	@echo "    make dev          - Start Next.js webapp"
+	@echo "    make up           - Start Docker services"
+	@echo ""
+	@grep -E '^[a-zA-Z_.%-]+:.*?## .*$$' $(MAKEFILE_LIST) | \
+		awk 'BEGIN {FS = ":.*?## "}; {printf "  %-22s %s\n", $$1, $$2}'

README.md

@@ -0,0 +1,155 @@
+# Ultiplate
+
+Template for any project: SaaS webapp, API server, ML pipeline, scraper, CLI, or background worker. AI-native, platform-agnostic, managed via Makefile + Nx.
+
+## Quick Start
+
+```bash
+cp .env.example .env        # fill in NAME and any keys you need
+make init                   # uv venv + sync + env linking
+make dev                    # Next.js webapp at http://localhost:3000
+make nx.projects            # list Nx projects in the monorepo
+```
+
+For Docker services (redis, ml inference, worker):
+```bash
+make up
+```
+
+## Directory
+
+```
+apps/
+  webapp/          Next.js 15 + React 19 + Tailwind 4 + Supabase auth (Bun, Turbopack)
+  webapp-minimal/  Streamlit quick prototype
+  backend/
+    fastapi/       FastAPI server (set BACKEND_MODE=fastapi)
+    flask/         Flask server  (set BACKEND_MODE=flask)
+  worker/          Celery background worker backed by Redis
+ml/
+  configs/         YAML config for data + training hyperparameters
+  models/          arch.py (architecture) + train.py (training loop)
+  data/            etl.py + processed artifacts
+  inference.py     FastAPI inference server
+  notebooks/       Jupyter notebooks
+alveslib/          Shared Python utilities (logger, scraper, agent)
+src/               Simple scripts / CLI entry points
+```
+
+## Make Targets
+
+| Target | Description |
+|--------|-------------|
+| `make init` | First-time setup |
+| `make dev` | Start Next.js webapp |
+| `make up` | Start Docker core services |
+| `make run.backend` | Start API backend |
+| `make run.worker` | Start Celery worker |
+| `make nx.graph` | Open Nx project graph |
+| `make nx.affected` | Run lint/test/build for affected projects |
+| `make lift.minio` | Start MinIO object storage |
+| `make lift.logging` | Start Loki + Grafana |
+| `make lift.mlflow` | Start optional MLflow server |
+| `make lift.database` | Start Postgres / MongoDB |
+| `make doctor` | Verify toolchain |
+
+Run `make help` for the full list.
+
+## Nx Workspace
+
+This template now ships with Nx project definitions for:
+
+- `webapp` (`apps/webapp`)
+- `webapp-minimal` (`apps/webapp-minimal`)
+- `backend-fastapi` (`apps/backend/fastapi`)
+- `backend-flask` (`apps/backend/flask`)
+- `worker` (`apps/worker`)
+- `ml` (`ml`)
+- `alveslib` (`alveslib`)
+
+Common commands:
+
+```bash
+bun x nx show projects
+bun x nx graph
+bun x nx run webapp:dev
+bun x nx affected -t lint,test,build
+```
+
+## AI Agent Capacity
+
+Set `ANTHROPIC_API_KEY` in `.env`. Then use:
+
+```python
+from alveslib import ask, stream, Agent
+
+# One-shot
+print(ask("Summarize this data: ..."))
+
+# Streaming
+for chunk in stream("Write a Celery task that ..."):
+    print(chunk, end="", flush=True)
+
+# Multi-turn
+agent = Agent(system="You are a senior Python developer.")
+agent.chat("Scaffold a FastAPI endpoint for user profiles")
+agent.chat("Add input validation and error handling")
+```
+
+Claude Code slash commands (type `/` in a Claude Code session):
+- `/plan` - implementation plan for an idea within this boilerplate
+- `/build` - implement a feature end-to-end
+- `/api` - scaffold a new backend endpoint
+- `/page` - scaffold a new Next.js page
+- `/review` - code review of recent changes
+- `/ship` - stage and commit changes
+
+## Logging
+
+```python
+from alveslib import get_logger
+logger = get_logger("service")
+```
+
+Outputs structured JSON to console + `./logs/`. Optional Loki push when `LOKI_PORT` is set and `make lift.logging` is running. View in Grafana at `http://localhost:$GRAFANA_PORT` (add Loki data source: `http://loki:3100`).
+
+## Python Packaging
+
+Python dependencies are managed with `pyproject.toml` and `uv`.
+
+```bash
+make deps         # uv sync
+make lock         # refresh uv.lock
+uv run pytest -v
+```
+
+## ML Workflow
+
+High-level ML hyperparameters live in YAML configs:
+
+- `ml/configs/data/default.yaml`
+- `ml/configs/train/default.yaml`
+
+Run with Nx targets (cacheable with explicit inputs/outputs):
+
+```bash
+bun x nx run ml:etl
+bun x nx run ml:train
+```
+
+`ml:train` depends on `ml:etl`, and both targets cache artifacts in `ml/data/processed`, `ml/models/weights`, and `ml/tensorboard`.
+
+## Services (docker compose profiles)
+
+| Profile | Services | Command |
+|---------|----------|---------|
+| _(default)_ | redis, ml-inference, worker | `make up` |
+| `minio` | + MinIO object storage | `make lift.minio` |
+| `tensorboard` | + TensorBoard | `make lift.tensorboard` |
+| `mlflow` | + MLflow tracking server (optional) | `make lift.mlflow` |
+| `logging` | + Loki + Grafana | `make lift.logging` |
+| `database` | + Postgres + MongoDB | `make lift.database` |
+
+## Webapp Auth
+
+Auth is off by default (`NEXT_PUBLIC_REQUIRE_AUTH=false`). Set it to `true` and configure Supabase keys to enable session-based auth gating across all routes.

alveslib/__init__.py

@@ -0,0 +1,4 @@
+from .logger import get_logger
+from .agent import ask, stream, ask_async, stream_async, Agent
+
+__all__ = ["get_logger", "ask", "stream", "ask_async", "stream_async", "Agent"]

alveslib/agent.py

@@ -0,0 +1,139 @@
+"""
+Thin async + sync wrappers over the Anthropic SDK for quick scripting and agent
+patterns. Use this when you want direct API access with streaming; for full
+agentic loops with file tools use `claude-agent-sdk` (pip install claude-agent-sdk).
+
+Usage:
+    from alveslib.agent import ask, stream, Agent
+
+    # One-shot
+    reply = ask("Summarize this data: ...")
+
+    # Streaming to stdout
+    stream("Write a FastAPI endpoint that ...")
+
+    # Multi-turn agent
+    agent = Agent(system="You are an expert Python dev.")
+    reply = agent.chat("Generate a Celery task that processes CSV files")
+    follow = agent.chat("Now add error handling and retries")
+"""
+
+import os
+import asyncio
+from typing import Iterator, AsyncIterator
+
+try:
+    import anthropic
+
+    _client: anthropic.Anthropic | None = anthropic.Anthropic(
+        api_key=os.environ.get("ANTHROPIC_API_KEY")
+    )
+    _async_client: anthropic.AsyncAnthropic | None = anthropic.AsyncAnthropic(
+        api_key=os.environ.get("ANTHROPIC_API_KEY")
+    )
+except ImportError:
+    _client = None
+    _async_client = None
+
+
+DEFAULT_MODEL = "claude-sonnet-4-5"
+
+
+def _require_client() -> "anthropic.Anthropic":
+    if _client is None:
+        raise ImportError("pip install anthropic")
+    if not os.environ.get("ANTHROPIC_API_KEY"):
+        raise RuntimeError("ANTHROPIC_API_KEY not set")
+    return _client
+
+
+def ask(prompt: str, system: str = "", model: str = DEFAULT_MODEL) -> str:
+    """One-shot blocking request; returns full text."""
+    client = _require_client()
+    msg = client.messages.create(
+        model=model,
+        max_tokens=8096,
+        system=system or anthropic.NOT_GIVEN,
+        messages=[{"role": "user", "content": prompt}],
+    )
+    return msg.content[0].text
+
+
+def stream(prompt: str, system: str = "", model: str = DEFAULT_MODEL) -> Iterator[str]:
+    """Streaming generator; yields text deltas. Print as they arrive."""
+    client = _require_client()
+    with client.messages.stream(
+        model=model,
+        max_tokens=8096,
+        system=system or anthropic.NOT_GIVEN,
+        messages=[{"role": "user", "content": prompt}],
+    ) as s:
+        yield from s.text_stream
+
+
+async def ask_async(prompt: str, system: str = "", model: str = DEFAULT_MODEL) -> str:
+    """Async one-shot request."""
+    if _async_client is None:
+        raise ImportError("pip install anthropic")
+    msg = await _async_client.messages.create(
+        model=model,
+        max_tokens=8096,
+        system=system or anthropic.NOT_GIVEN,
+        messages=[{"role": "user", "content": prompt}],
+    )
+    return msg.content[0].text
+
+
+async def stream_async(
+    prompt: str, system: str = "", model: str = DEFAULT_MODEL
+) -> AsyncIterator[str]:
+    """Async streaming generator."""
+    if _async_client is None:
+        raise ImportError("pip install anthropic")
+    async with _async_client.messages.stream(
+        model=model,
+        max_tokens=8096,
+        system=system or anthropic.NOT_GIVEN,
+        messages=[{"role": "user", "content": prompt}],
+    ) as s:
+        async for text in s.text_stream:
+            yield text
+
+
+class Agent:
+    """Stateful multi-turn conversation agent with optional system prompt."""
+
+    def __init__(self, system: str = "", model: str = DEFAULT_MODEL):
+        self.system = system
+        self.model = model
+        self.history: list[dict] = []
+
+    def chat(self, prompt: str) -> str:
+        client = _require_client()
+        self.history.append({"role": "user", "content": prompt})
+        msg = client.messages.create(
+            model=self.model,
+            max_tokens=8096,
+            system=self.system or anthropic.NOT_GIVEN,
+            messages=self.history,
+        )
+        reply = msg.content[0].text
+        self.history.append({"role": "assistant", "content": reply})
+        return reply
+
+    async def chat_async(self, prompt: str) -> str:
+        if _async_client is None:
+            raise ImportError("pip install anthropic")
+        self.history.append({"role": "user", "content": prompt})
+        msg = await _async_client.messages.create(
+            model=self.model,
+            max_tokens=8096,
+            system=self.system or anthropic.NOT_GIVEN,
+            messages=self.history,
+        )
+        reply = msg.content[0].text
+        self.history.append({"role": "assistant", "content": reply})
+        return reply
+
+    def reset(self) -> None:
+        self.history.clear()

alveslib/logger.py

@@ -0,0 +1,83 @@
+import json
+import logging
+import os
+from datetime import datetime
+from pathlib import Path
+
+try:
+    from dotenv import load_dotenv
+    load_dotenv()
+except ImportError:
+    pass
+
+try:
+    from logging_loki import LokiHandler
+    LOKI_AVAILABLE = True
+except ImportError:
+    LOKI_AVAILABLE = False
+
+def get_logger(service_name: str, level: str = "INFO") -> logging.Logger:
+    """
+    Get a configured logger for UltiPlate services.
+
+    Args:
+        service_name: Name of the service/module
+        level: Log level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
+
+    Returns:
+        Configured logger instance
+    """
+    logger = logging.getLogger(service_name)
+    logger.setLevel(getattr(logging, level.upper()))
+
+    if not logger.handlers:
+        # Console handler with JSON formatting
+        handler = logging.StreamHandler()
+        handler.setFormatter(JsonFormatter(service_name))
+        logger.addHandler(handler)
+
+        # File handler - writes to logs directory
+        logs_dir = Path(os.getenv("LOGDIR", "./logs"))
+        logs_dir.mkdir(parents=True, exist_ok=True)
+        file_handler = logging.FileHandler(logs_dir / f"{service_name}.log")
+        file_handler.setFormatter(JsonFormatter(service_name))
+        logger.addHandler(file_handler)
+
+        # Loki handler - sends logs directly to Loki
+        if LOKI_AVAILABLE:
+            loki_port = os.getenv("LOKI_PORT", "3100")
+            loki_url = f"http://localhost:{loki_port}/loki/api/v1/push"
+
+            try:
+                loki_handler = LokiHandler(
+                    url=loki_url,
+                    tags={"service": service_name},
+                    version="1"
+                )
+                logger.addHandler(loki_handler)
+            except Exception as e:
+                # If Loki is not available, just continue with file/console logging
+                pass
+
+    return logger
+
+class JsonFormatter(logging.Formatter):
+    def __init__(self, service_name: str):
+        super().__init__()
+        self.service_name = service_name
+
+    def format(self, record):
+        log_entry = {
+            "timestamp": datetime.utcnow().isoformat() + "Z",
+            "service": self.service_name,
+            "level": record.levelname,
+            "message": record.getMessage(),
+            "module": record.module,
+            "function": record.funcName,
+            "line": record.lineno
+        }
+
+        if record.exc_info:
+            log_entry["exception"] = self.formatException(record.exc_info)
+
+        return json.dumps(log_entry)

alveslib/project.json

@@ -0,0 +1,32 @@
+{
+  "name": "alveslib",
+  "root": "alveslib",
+  "sourceRoot": "alveslib",
+  "projectType": "library",
+  "targets": {
+    "build": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "python3.12 -m compileall alveslib"
+      }
+    },
+    "lint": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/ruff check alveslib"
+      }
+    },
+    "typecheck": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/mypy alveslib"
+      }
+    },
+    "test": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/pytest alveslib -v"
+      }
+    }
+  }
+}

alveslib/scraper.py

@@ -0,0 +1,70 @@
+import hashlib
+import pickle
+import os
+from pathlib import Path
+from seleniumbase import SB
+from bs4 import BeautifulSoup
+from typing import Optional
+
+class ScraperCache:
+    def __init__(self, cache_dir: str = ".scraper_cache"):
+        self.cache_dir = Path(cache_dir)
+        self.cache_dir.mkdir(exist_ok=True)
+
+    def _get_cache_key(self, url: str) -> str:
+        return hashlib.md5(url.encode()).hexdigest()
+
+    def _get_cache_path(self, cache_key: str) -> Path:
+        return self.cache_dir / f"{cache_key}.pkl"
+
+    def get(self, url: str) -> Optional[BeautifulSoup]:
+        cache_key = self._get_cache_key(url)
+        cache_path = self._get_cache_path(cache_key)
+
+        if cache_path.exists():
+            try:
+                with open(cache_path, 'rb') as f:
+                    return pickle.load(f)
+            except:
+                pass
+        return None
+
+    def set(self, url: str, soup: BeautifulSoup) -> None:
+        cache_key = self._get_cache_key(url)
+        cache_path = self._get_cache_path(cache_key)
+
+        try:
+            with open(cache_path, 'wb') as f:
+                pickle.dump(soup, f)
+        except:
+            pass
+
+_cache = ScraperCache() # glob
+
+def scrape_url(url: str, use_cache: bool = True) -> BeautifulSoup:
+    if use_cache:
+        cached_soup = _cache.get(url)
+        if cached_soup:
+            return cached_soup
+
+    with SB(test=True, uc=True) as sb:
+        sb.open(url)
+        html = sb.get_page_source()
+        soup = BeautifulSoup(html, 'html.parser')
+
+        if use_cache:
+            _cache.set(url, soup)
+
+        return soup
+
+
+
+if __name__ == "__main__":
+    url = "https://httpbin.org/html"
+    print("Testing scraper...")
+    soup = scrape_url(url)
+    print(f"Title: {soup.title.text if soup.title else 'No title'}")
+    print(f"Found {len(soup.find_all('p'))} paragraphs")
+    print("\nTesting cache...")
+    soup2 = scrape_url(url)
+    print("Cache test completed")

apps/backend/fastapi/project.json

@@ -0,0 +1,40 @@
+{
+  "name": "backend-fastapi",
+  "root": "apps/backend/fastapi",
+  "sourceRoot": "apps/backend/fastapi",
+  "projectType": "application",
+  "implicitDependencies": ["alveslib"],
+  "targets": {
+    "dev": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/backend/fastapi",
+        "command": "python3.12 server.py"
+      }
+    },
+    "build": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "python3.12 -m compileall apps/backend/fastapi"
+      }
+    },
+    "lint": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/ruff check apps/backend/fastapi"
+      }
+    },
+    "typecheck": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/mypy apps/backend/fastapi"
+      }
+    },
+    "test": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/pytest apps/backend/fastapi -v"
+      }
+    }
+  }
+}

apps/backend/fastapi/server.py

@@ -0,0 +1,24 @@
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+import uvicorn
+import os
+from dotenv import load_dotenv
+load_dotenv()
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+@app.get("/health")
+async def health():
+    return {"status": "healthy"}
+
+if __name__ == "__main__":
+    PORT=int(os.getenv("BACKEND_PORT", 5000))
+    uvicorn.run("server:app", host="0.0.0.0", port=PORT, reload=True)

apps/backend/flask/project.json

@@ -0,0 +1,40 @@
+{
+  "name": "backend-flask",
+  "root": "apps/backend/flask",
+  "sourceRoot": "apps/backend/flask",
+  "projectType": "application",
+  "implicitDependencies": ["alveslib"],
+  "targets": {
+    "dev": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/backend/flask",
+        "command": "python3.12 server.py"
+      }
+    },
+    "build": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "python3.12 -m compileall apps/backend/flask"
+      }
+    },
+    "lint": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/ruff check apps/backend/flask"
+      }
+    },
+    "typecheck": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/mypy apps/backend/flask"
+      }
+    },
+    "test": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/pytest apps/backend/flask -v"
+      }
+    }
+  }
+}

apps/backend/flask/server.py

@@ -0,0 +1,17 @@
+from flask import Flask
+from flask_cors import CORS
+import os
+from dotenv import load_dotenv
+load_dotenv()
+
+app = Flask(__name__)
+CORS(app, origins="*")
+
+@app.route('/health')
+def health():
+    return {'status': 'healthy'}, 200
+
+
+if __name__ == '__main__':
+    PORT=int(os.getenv("BACKEND_PORT", 5000))
+    app.run(host='0.0.0.0', port=PORT, debug=True)

apps/webapp-minimal/app.py

@@ -0,0 +1 @@
+import streamlit as st

apps/webapp-minimal/project.json

@@ -0,0 +1,15 @@
+{
+  "name": "webapp-minimal",
+  "root": "apps/webapp-minimal",
+  "sourceRoot": "apps/webapp-minimal",
+  "projectType": "application",
+  "targets": {
+    "dev": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/webapp-minimal",
+        "command": "streamlit run app.py"
+      }
+    }
+  }
+}

apps/webapp/.gitignore

@@ -0,0 +1,16 @@
+/node_modules
+/.next/
+/out/
+/build
+/coverage
+.DS_Store
+*.pem
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+.pnpm-debug.log*
+.env*
+.vercel
+*.tsbuildinfo
+next-env.d.ts
+package-lock.json

apps/webapp/README.md

@@ -0,0 +1,36 @@
+Next.js 15 webapp with React 19, Tailwind CSS 4, Supabase auth, and Turbopack.
+
+## Start
+
+```bash
+bun dev
+# or from project root: make run.webapp
+```
+
+Open [http://localhost:3000](http://localhost:3000).
+
+## Scripts
+
+| Command | Description |
+|---------|-------------|
+| `bun dev` | Dev server with Turbopack |
+| `bun build` | Production build |
+| `bun start` | Serve production build |
+| `bun lint` | Run ESLint |
+| `bun typecheck` | Run tsc --noEmit |
+
+## Auth
+
+Auth is wired to Supabase via `NEXT_PUBLIC_SUPABASE_URL` and `NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY`.
+Set `NEXT_PUBLIC_REQUIRE_AUTH=false` in `.env` to disable auth-gating entirely (default for quick prototyping).
+
+## Structure
+
+```
+src/
+  app/           - Next.js App Router pages
+  components/    - Reusable bare-bones components (style last)
+  utils/supabase - Supabase client helpers
+  libs/          - Shared utilities
+  locales/       - i18n strings (add languages as needed)
+```

apps/webapp/bun.lock

@@ -0,0 +1,862 @@
+{
+  "lockfileVersion": 1,
+  "configVersion": 0,
+  "workspaces": {
+    "": {
+      "name": "webapp",
+      "dependencies": {
+        "@supabase/ssr": "^0.7.0",
+        "@supabase/supabase-js": "^2.57.4",
+        "next": "15.5.2",
+        "react": "19.1.0",
+        "react-dom": "19.1.0",
+      },
+      "devDependencies": {
+        "@eslint/eslintrc": "^3",
+        "@tailwindcss/postcss": "^4",
+        "@types/node": "^20",
+        "@types/react": "^19",
+        "@types/react-dom": "^19",
+        "eslint": "^9",
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+    "@eslint-community/eslint-utils/eslint-visitor-keys": ["eslint-visitor-keys@3.4.3", "", {}, "sha512-wpc+LXeiyiisxPlEkUzU6svyS1frIO3Mgxj1fdy7Pm8Ygzguax2N3Fa/D/ag1WqbOprdI+uY6wMUl8/a2G+iag=="],
+
+    "@typescript-eslint/eslint-plugin/ignore": ["ignore@7.0.5", "", {}, "sha512-Hs59xBNfUIunMFgWAbGX5cq6893IbWg4KnrjbYwX3tx0ztorVgTDA6B2sxf8ejHJ4wz8BqGUMYlnzNBer5NvGg=="],
+
+    "@typescript-eslint/typescript-estree/fast-glob": ["fast-glob@3.3.3", "", { "dependencies": { "@nodelib/fs.stat": "^2.0.2", "@nodelib/fs.walk": "^1.2.3", "glob-parent": "^5.1.2", "merge2": "^1.3.0", "micromatch": "^4.0.8" } }, "sha512-7MptL8U0cqcFdzIzwOTHoilX9x5BrNqye7Z/LuC7kCMRio1EMSyqRK3BEAUD7sXRq4iT4AzTVuZdhgQ2TCvYLg=="],
+
+    "@typescript-eslint/typescript-estree/minimatch": ["minimatch@9.0.5", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow=="],
+
+    "@typescript-eslint/typescript-estree/semver": ["semver@7.7.2", "", { "bin": "bin/semver.js" }, "sha512-RF0Fw+rO5AMf9MAyaRXI4AV0Ulj5lMHqVxxdSgiVbixSCXoEmmX/jk0CuJw4+3SqroYO9VoUh+HcuJivvtJemA=="],
+
+    "eslint-import-resolver-node/debug": ["debug@3.2.7", "", { "dependencies": { "ms": "^2.1.1" } }, "sha512-CFjzYYAi4ThfiQvizrFQevTTXHtnCqWfe7x1AhgEscTz6ZbLbfoLRLPugTQyBth6f8ZERVUSyWHFD/7Wu4t1XQ=="],
+
+    "eslint-module-utils/debug": ["debug@3.2.7", "", { "dependencies": { "ms": "^2.1.1" } }, "sha512-CFjzYYAi4ThfiQvizrFQevTTXHtnCqWfe7x1AhgEscTz6ZbLbfoLRLPugTQyBth6f8ZERVUSyWHFD/7Wu4t1XQ=="],
+
+    "eslint-plugin-import/debug": ["debug@3.2.7", "", { "dependencies": { "ms": "^2.1.1" } }, "sha512-CFjzYYAi4ThfiQvizrFQevTTXHtnCqWfe7x1AhgEscTz6ZbLbfoLRLPugTQyBth6f8ZERVUSyWHFD/7Wu4t1XQ=="],
+
+    "eslint-plugin-react/resolve": ["resolve@2.0.0-next.5", "", { "dependencies": { "is-core-module": "^2.13.0", "path-parse": "^1.0.7", "supports-preserve-symlinks-flag": "^1.0.0" }, "bin": "bin/resolve" }, "sha512-U7WjGVG9sH8tvjW5SmGbQuui75FiyjAX72HX15DwBBwF9dNiQZRQAg9nnPhYy+TUnE0+VcrttuvNI8oSxZcocA=="],
+
+    "eslint-plugin-react/semver": ["semver@6.3.1", "", { "bin": "bin/semver.js" }, "sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA=="],
+
+    "fast-glob/glob-parent": ["glob-parent@5.1.2", "", { "dependencies": { "is-glob": "^4.0.1" } }, "sha512-AOIgSQCepiJYwP3ARnGx+5VnTu2HBYdzbGP45eLw1vr3zB3vZLeyed1sC9hnbcOc9/SrMyM5RPQrkGz4aS9Zow=="],
+
+    "is-bun-module/semver": ["semver@7.7.2", "", { "bin": "bin/semver.js" }, "sha512-RF0Fw+rO5AMf9MAyaRXI4AV0Ulj5lMHqVxxdSgiVbixSCXoEmmX/jk0CuJw4+3SqroYO9VoUh+HcuJivvtJemA=="],
+
+    "micromatch/picomatch": ["picomatch@2.3.1", "", {}, "sha512-JU3teHTNjmE2VCGFzuY8EXzCDVwEqB2a8fsIvwaStHhAWJEeVd1o1QD80CU6+ZdEXXSLbSsuLwJjkCBWqRQUVA=="],
+
+    "next/postcss": ["postcss@8.4.31", "", { "dependencies": { "nanoid": "^3.3.6", "picocolors": "^1.0.0", "source-map-js": "^1.0.2" } }, "sha512-PS08Iboia9mts/2ygV3eLpY5ghnUcfLV/EXTOW1E2qYxJKGGBUtNjN76FYHnMs36RmARn41bC0AZmn+rR0OVpQ=="],
+
+    "sharp/semver": ["semver@7.7.2", "", { "bin": "bin/semver.js" }, "sha512-RF0Fw+rO5AMf9MAyaRXI4AV0Ulj5lMHqVxxdSgiVbixSCXoEmmX/jk0CuJw4+3SqroYO9VoUh+HcuJivvtJemA=="],
+
+    "@typescript-eslint/typescript-estree/fast-glob/glob-parent": ["glob-parent@5.1.2", "", { "dependencies": { "is-glob": "^4.0.1" } }, "sha512-AOIgSQCepiJYwP3ARnGx+5VnTu2HBYdzbGP45eLw1vr3zB3vZLeyed1sC9hnbcOc9/SrMyM5RPQrkGz4aS9Zow=="],
+
+    "@typescript-eslint/typescript-estree/minimatch/brace-expansion": ["brace-expansion@2.0.2", "", { "dependencies": { "balanced-match": "^1.0.0" } }, "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ=="],
+  }
+}

apps/webapp/eslint.config.mjs

@@ -0,0 +1,25 @@
+import { dirname } from "path";
+import { fileURLToPath } from "url";
+import { FlatCompat } from "@eslint/eslintrc";
+
+const __filename = fileURLToPath(import.meta.url);
+const __dirname = dirname(__filename);
+
+const compat = new FlatCompat({
+  baseDirectory: __dirname,
+});
+
+const eslintConfig = [
+  ...compat.extends("next/core-web-vitals", "next/typescript"),
+  {
+    ignores: [
+      "node_modules/**",
+      ".next/**",
+      "out/**",
+      "build/**",
+      "next-env.d.ts",
+    ],
+  },
+];
+
+export default eslintConfig;

apps/webapp/middleware.ts

@@ -0,0 +1,16 @@
+import { type NextRequest, NextResponse } from 'next/server'
+import { updateSession } from '@/utils/supabase/middleware'
+
+export async function middleware(request: NextRequest) {
+  // Set NEXT_PUBLIC_REQUIRE_AUTH=true in .env to enable Supabase auth gating
+  if (process.env.NEXT_PUBLIC_REQUIRE_AUTH !== 'true') {
+    return NextResponse.next({ request })
+  }
+  return await updateSession(request)
+}
+
+export const config = {
+  matcher: [
+    '/((?!_next/static|_next/image|favicon.ico|.*\\.(?:svg|png|jpg|jpeg|gif|webp)$).*)',
+  ],
+}

apps/webapp/next.config.ts

@@ -0,0 +1,8 @@
+import type { NextConfig } from "next";
+import path from "node:path";
+
+const nextConfig: NextConfig = {
+  outputFileTracingRoot: path.join(process.cwd(), "../.."),
+};
+
+export default nextConfig;

apps/webapp/package.json

@@ -0,0 +1,31 @@
+{
+  "name": "webapp",
+  "version": "0.1.0",
+  "private": true,
+  "packageManager": "bun@1.2.0",
+  "scripts": {
+    "dev": "next dev --turbopack",
+    "build": "next build",
+    "start": "next start",
+    "lint": "eslint",
+    "typecheck": "tsc --noEmit"
+  },
+  "dependencies": {
+    "@supabase/ssr": "^0.7.0",
+    "@supabase/supabase-js": "^2.57.4",
+    "next": "15.5.2",
+    "react": "19.1.0",
+    "react-dom": "19.1.0"
+  },
+  "devDependencies": {
+    "@eslint/eslintrc": "^3",
+    "@tailwindcss/postcss": "^4",
+    "@types/node": "^20",
+    "@types/react": "^19",
+    "@types/react-dom": "^19",
+    "eslint": "^9",
+    "eslint-config-next": "15.5.2",
+    "tailwindcss": "^4",
+    "typescript": "^5"
+  }
+}

apps/webapp/postcss.config.mjs

@@ -0,0 +1,5 @@
+const config = {
+  plugins: ["@tailwindcss/postcss"],
+};
+
+export default config;

apps/webapp/project.json

@@ -0,0 +1,44 @@
+{
+  "name": "webapp",
+  "root": "apps/webapp",
+  "sourceRoot": "apps/webapp/src",
+  "projectType": "application",
+  "targets": {
+    "dev": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/webapp",
+        "command": "bun run dev"
+      }
+    },
+    "build": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/webapp",
+        "command": "bun run build"
+      },
+      "outputs": ["{projectRoot}/.next"]
+    },
+    "start": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/webapp",
+        "command": "bun run start"
+      }
+    },
+    "lint": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/webapp",
+        "command": "bun run lint"
+      }
+    },
+    "typecheck": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/webapp",
+        "command": "bun run typecheck"
+      }
+    }
+  }
+}

apps/webapp/public/file.svg

@@ -0,0 +1 @@
+<svg fill="none" viewBox="0 0 16 16" xmlns="http://www.w3.org/2000/svg"><path d="M14.5 13.5V5.41a1 1 0 0 0-.3-.7L9.8.29A1 1 0 0 0 9.08 0H1.5v13.5A2.5 2.5 0 0 0 4 16h8a2.5 2.5 0 0 0 2.5-2.5m-1.5 0v-7H8v-5H3v12a1 1 0 0 0 1 1h8a1 1 0 0 0 1-1M9.5 5V2.12L12.38 5zM5.13 5h-.62v1.25h2.12V5zm-.62 3h7.12v1.25H4.5zm.62 3h-.62v1.25h7.12V11z" clip-rule="evenodd" fill="#666" fill-rule="evenodd"/></svg>

apps/webapp/public/globe.svg

@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><g clip-path="url(#a)"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.27 14.1a6.5 6.5 0 0 0 3.67-3.45q-1.24.21-2.7.34-.31 1.83-.97 3.1M8 16A8 8 0 1 0 8 0a8 8 0 0 0 0 16m.48-1.52a7 7 0 0 1-.96 0H7.5a4 4 0 0 1-.84-1.32q-.38-.89-.63-2.08a40 40 0 0 0 3.92 0q-.25 1.2-.63 2.08a4 4 0 0 1-.84 1.31zm2.94-4.76q1.66-.15 2.95-.43a7 7 0 0 0 0-2.58q-1.3-.27-2.95-.43a18 18 0 0 1 0 3.44m-1.27-3.54a17 17 0 0 1 0 3.64 39 39 0 0 1-4.3 0 17 17 0 0 1 0-3.64 39 39 0 0 1 4.3 0m1.1-1.17q1.45.13 2.69.34a6.5 6.5 0 0 0-3.67-3.44q.65 1.26.98 3.1M8.48 1.5l.01.02q.41.37.84 1.31.38.89.63 2.08a40 40 0 0 0-3.92 0q.25-1.2.63-2.08a4 4 0 0 1 .85-1.32 7 7 0 0 1 .96 0m-2.75.4a6.5 6.5 0 0 0-3.67 3.44 29 29 0 0 1 2.7-.34q.31-1.83.97-3.1M4.58 6.28q-1.66.16-2.95.43a7 7 0 0 0 0 2.58q1.3.27 2.95.43a18 18 0 0 1 0-3.44m.17 4.71q-1.45-.12-2.69-.34a6.5 6.5 0 0 0 3.67 3.44q-.65-1.27-.98-3.1" fill="#666"/></g><defs><clipPath id="a"><path fill="#fff" d="M0 0h16v16H0z"/></clipPath></defs></svg>

apps/webapp/public/llms.txt

@@ -0,0 +1 @@
+This is a project by Daniel Alves Rosel (https://alves.world)

apps/webapp/public/next.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 394 80"><path fill="#000" d="M262 0h68.5v12.7h-27.2v66.6h-13.6V12.7H262V0ZM149 0v12.7H94v20.4h44.3v12.6H94v21h55v12.6H80.5V0h68.7zm34.3 0h-17.8l63.8 79.4h17.9l-32-39.7 32-39.6h-17.9l-23 28.6-23-28.6zm18.3 56.7-9-11-27.1 33.7h17.8l18.3-22.7z"/><path fill="#000" d="M81 79.3 17 0H0v79.3h13.6V17l50.2 62.3H81Zm252.6-.4c-1 0-1.8-.4-2.5-1s-1.1-1.6-1.1-2.6.3-1.8 1-2.5 1.6-1 2.6-1 1.8.3 2.5 1a3.4 3.4 0 0 1 .6 4.3 3.7 3.7 0 0 1-3 1.8zm23.2-33.5h6v23.3c0 2.1-.4 4-1.3 5.5a9.1 9.1 0 0 1-3.8 3.5c-1.6.8-3.5 1.3-5.7 1.3-2 0-3.7-.4-5.3-1s-2.8-1.8-3.7-3.2c-.9-1.3-1.4-3-1.4-5h6c.1.8.3 1.6.7 2.2s1 1.2 1.6 1.5c.7.4 1.5.5 2.4.5 1 0 1.8-.2 2.4-.6a4 4 0 0 0 1.6-1.8c.3-.8.5-1.8.5-3V45.5zm30.9 9.1a4.4 4.4 0 0 0-2-3.3 7.5 7.5 0 0 0-4.3-1.1c-1.3 0-2.4.2-3.3.5-.9.4-1.6 1-2 1.6a3.5 3.5 0 0 0-.3 4c.3.5.7.9 1.3 1.2l1.8 1 2 .5 3.2.8c1.3.3 2.5.7 3.7 1.2a13 13 0 0 1 3.2 1.8 8.1 8.1 0 0 1 3 6.5c0 2-.5 3.7-1.5 5.1a10 10 0 0 1-4.4 3.5c-1.8.8-4.1 1.2-6.8 1.2-2.6 0-4.9-.4-6.8-1.2-2-.8-3.4-2-4.5-3.5a10 10 0 0 1-1.7-5.6h6a5 5 0 0 0 3.5 4.6c1 .4 2.2.6 3.4.6 1.3 0 2.5-.2 3.5-.6 1-.4 1.8-1 2.4-1.7a4 4 0 0 0 .8-2.4c0-.9-.2-1.6-.7-2.2a11 11 0 0 0-2.1-1.4l-3.2-1-3.8-1c-2.8-.7-5-1.7-6.6-3.2a7.2 7.2 0 0 1-2.4-5.7 8 8 0 0 1 1.7-5 10 10 0 0 1 4.3-3.5c2-.8 4-1.2 6.4-1.2 2.3 0 4.4.4 6.2 1.2 1.8.8 3.2 2 4.3 3.4 1 1.4 1.5 3 1.5 5h-5.8z"/></svg>

apps/webapp/public/vercel.svg

@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1155 1000"><path d="m577.3 0 577.4 1000H0z" fill="#fff"/></svg>

apps/webapp/public/window.svg

@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" clip-rule="evenodd" d="M1.5 2.5h13v10a1 1 0 0 1-1 1h-11a1 1 0 0 1-1-1zM0 1h16v11.5a2.5 2.5 0 0 1-2.5 2.5h-11A2.5 2.5 0 0 1 0 12.5zm3.75 4.5a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5M7 4.75a.75.75 0 1 1-1.5 0 .75.75 0 0 1 1.5 0m1.75.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5" fill="#666"/></svg>

apps/webapp/src/app/auth/confirm/route.ts

@@ -0,0 +1,28 @@
+import { type EmailOtpType } from '@supabase/supabase-js'
+import { type NextRequest } from 'next/server'
+
+import { createClient } from '@/utils/supabase/server'
+import { redirect } from 'next/navigation'
+
+export async function GET(request: NextRequest) {
+  const { searchParams } = new URL(request.url)
+  const token_hash = searchParams.get('token_hash')
+  const type = searchParams.get('type') as EmailOtpType | null
+  const next = searchParams.get('next') ?? '/'
+
+  if (token_hash && type) {
+    const supabase = await createClient()
+
+    const { error } = await supabase.auth.verifyOtp({
+      type,
+      token_hash,
+    })
+    if (!error) {
+      // redirect user to specified redirect URL or root of app
+      redirect(next)
+    }
+  }
+
+  // redirect the user to an error page with some instructions
+  redirect('/error')
+}

apps/webapp/src/app/blog/page.tsx

@@ -0,0 +1,10 @@
+export default function BlogPage() {
+  return (
+    <main className="mx-auto max-w-3xl px-6 py-16">
+      <h1 className="text-3xl font-semibold tracking-tight">Blog</h1>
+      <p className="mt-4 text-sm text-neutral-600">
+        Publish product updates, engineering notes, and launch posts here.
+      </p>
+    </main>
+  );
+}

apps/webapp/src/app/dashboard/actions.ts

@@ -0,0 +1,12 @@
+'use server'
+
+import { revalidatePath } from 'next/cache'
+import { redirect } from 'next/navigation'
+import { createClient } from '@/utils/supabase/server'
+
+export async function logout() {
+  const supabase = await createClient()
+  await supabase.auth.signOut()
+  revalidatePath('/', 'layout')
+  redirect('/login')
+}

apps/webapp/src/app/dashboard/layout.tsx

@@ -0,0 +1,14 @@
+export default function DashboardLayout({
+  children,
+}: {
+  children: React.ReactNode
+}) {
+  return (
+    <div>
+      <nav>
+        <h1>Dashboard</h1>
+      </nav>
+      <main>{children}</main>
+    </div>
+  )
+}

apps/webapp/src/app/dashboard/page.tsx

@@ -0,0 +1,21 @@
+import { redirect } from 'next/navigation'
+import { createClient } from '@/utils/supabase/server'
+import { logout } from './actions'
+
+export default async function DashboardPage() {
+  const supabase = await createClient()
+
+  const { data, error } = await supabase.auth.getUser()
+  if (error || !data?.user) {
+    redirect('/login')
+  }
+
+  return (
+    <div>
+      <p>Welcome, {data.user.email}</p>
+      <form>
+        <button formAction={logout}>Logout</button>
+      </form>
+    </div>
+  )
+}

apps/webapp/src/app/error.tsx

@@ -0,0 +1,20 @@
+'use client';
+
+export default function Error({
+  error,
+  reset,
+}: {
+  error: Error & { digest?: string };
+  reset: () => void;
+}) {
+  return (
+    <div>
+      {/* TODO: Style this error page when implementing in your project */}
+      <h2>Something went wrong!</h2>
+      <p>{error.message || 'An unexpected error occurred'}</p>
+      <button onClick={() => reset()}>
+        Try again
+      </button>
+    </div>
+  );
+}

apps/webapp/src/app/error/page.tsx

@@ -0,0 +1,5 @@
+'use client'
+
+export default function ErrorPage() {
+  return <p>Sorry, something went wrong</p>
+}

apps/webapp/src/app/globals.css

@@ -0,0 +1,26 @@
+@import "tailwindcss";
+
+:root {
+  --background: #ffffff;
+  --foreground: #171717;
+}
+
+@theme inline {
+  --color-background: var(--background);
+  --color-foreground: var(--foreground);
+  --font-sans: var(--font-geist-sans);
+  --font-mono: var(--font-geist-mono);
+}
+
+@media (prefers-color-scheme: dark) {
+  :root {
+    --background: #0a0a0a;
+    --foreground: #ededed;
+  }
+}
+
+body {
+  background: var(--background);
+  color: var(--foreground);
+  font-family: Arial, Helvetica, sans-serif;
+}

apps/webapp/src/app/instruments/page.tsx

@@ -0,0 +1,8 @@
+import { createClient } from '@/utils/supabase/server';
+
+export default async function Instruments() {
+  const supabase = await createClient();
+  const { data: instruments } = await supabase.from("instruments").select();
+
+  return <pre>{JSON.stringify(instruments, null, 2)}</pre>
+}

apps/webapp/src/app/layout.tsx

@@ -0,0 +1,29 @@
+import type { Metadata } from "next";
+import "./globals.css";
+import Header from "@/components/Header";
+import Footer from "@/components/Footer";
+
+const fontVariables = "font-sans";
+
+export const metadata: Metadata = {
+    title: "Ultiplate - Ultimate Boilerplate",
+    description: "AI-native template for any project with deployment ready setup",
+};
+
+export default function RootLayout({
+    children,
+}: Readonly<{
+    children: React.ReactNode;
+}>) {
+    return (
+        <html lang="en">
+            <body className={`${fontVariables} antialiased`}>
+                <Header />
+                <main className="min-h-screen">
+                    {children}
+                </main>
+                <Footer />
+            </body>
+        </html>
+    );
+}

apps/webapp/src/app/login/actions.ts

@@ -0,0 +1,46 @@
+'use server'
+
+import { revalidatePath } from 'next/cache'
+import { redirect } from 'next/navigation'
+
+import { createClient } from '@/utils/supabase/server'
+
+export async function login(formData: FormData) {
+  const supabase = await createClient()
+
+  // type-casting here for convenience
+  // in practice, you should validate your inputs
+  const data = {
+    email: formData.get('email') as string,
+    password: formData.get('password') as string,
+  }
+
+  const { error } = await supabase.auth.signInWithPassword(data)
+
+  if (error) {
+    redirect('/error')
+  }
+
+  revalidatePath('/', 'layout')
+  redirect('/')
+}
+
+export async function signup(formData: FormData) {
+  const supabase = await createClient()
+
+  // type-casting here for convenience
+  // in practice, you should validate your inputs
+  const data = {
+    email: formData.get('email') as string,
+    password: formData.get('password') as string,
+  }
+
+  const { error } = await supabase.auth.signUp(data)
+
+  if (error) {
+    redirect('/error')
+  }
+
+  revalidatePath('/', 'layout')
+  redirect('/')
+}

apps/webapp/src/app/login/page.tsx

@@ -0,0 +1,14 @@
+import { login, signup } from './actions'
+
+export default function LoginPage() {
+  return (
+    <form>
+      <label htmlFor="email">Email:</label>
+      <input id="email" name="email" type="email" required />
+      <label htmlFor="password">Password:</label>
+      <input id="password" name="password" type="password" required />
+      <button formAction={login}>Log in</button>
+      <button formAction={signup}>Sign up</button>
+    </form>
+  )
+}

apps/webapp/src/app/not-found.tsx

@@ -0,0 +1,12 @@
+import Link from 'next/link';
+
+export default function NotFound() {
+  return (
+    <div>
+      {/* TODO: Style this 404 page when implementing in your project */}
+      <h2>Not Found</h2>
+      <p>Could not find requested resource</p>
+      <Link href="/">Return Home</Link>
+    </div>
+  );
+}

apps/webapp/src/app/page.tsx

@@ -0,0 +1,17 @@
+import Hero from "@/components/Hero";
+import FeaturesGrid from "@/components/FeaturesGrid";
+import Testimonials1 from "@/components/Testimonials1";
+import Pricing from "@/components/Pricing";
+//import FAQ from "@/components/FAQ";
+//import CTA from "@/components/CTA";
+
+export default function Home() {
+  return (
+    <div>
+      <Hero />
+      <FeaturesGrid />
+      <Testimonials1 />
+      <Pricing />
+    </div>
+  );
+}

apps/webapp/src/app/privacy-policy/page.tsx

@@ -0,0 +1,10 @@
+export default function PrivacyPolicyPage() {
+  return (
+    <main className="mx-auto max-w-3xl px-6 py-16">
+      <h1 className="text-3xl font-semibold tracking-tight">Privacy Policy</h1>
+      <p className="mt-4 text-sm text-neutral-600">
+        Describe what data you collect, how it is used, and how users can request deletion.
+      </p>
+    </main>
+  );
+}

apps/webapp/src/app/tos/page.tsx

@@ -0,0 +1,10 @@
+export default function TermsOfServicePage() {
+  return (
+    <main className="mx-auto max-w-3xl px-6 py-16">
+      <h1 className="text-3xl font-semibold tracking-tight">Terms of Service</h1>
+      <p className="mt-4 text-sm text-neutral-600">
+        Add your product terms, responsibilities, and legal limitations in this page.
+      </p>
+    </main>
+  );
+}

apps/webapp/src/components/FeaturesGrid.tsx

@@ -0,0 +1,22 @@
+import { getLocale } from "@/libs/locales";
+
+export default function FeaturesGrid() {
+  const { common } = getLocale('en');
+
+  return (
+    <section>
+      {/* TODO: Style this features grid when implementing in your project */}
+      <div>
+        <h2>{common.features.title}</h2>
+        <div>
+          {common.features.items.map((feature, index) => (
+            <div key={index}>
+              <h3>{feature.title}</h3>
+              <p>{feature.description}</p>
+            </div>
+          ))}
+        </div>
+      </div>
+    </section>
+  );
+}

apps/webapp/src/components/Footer.tsx

@@ -0,0 +1,37 @@
+import Link from "next/link";
+import { getLocale } from "@/libs/locales";
+
+export default function Footer() {
+  const { common } = getLocale('en');
+  
+  return (
+    <footer>
+      {/* TODO: Style this footer when implementing in your project */}
+      <div>
+        <div>
+          <div>
+            <h3>{common.footer.brand}</h3>
+            <p>{common.footer.description}</p>
+          </div>
+          <div>
+            <h4>{common.footer.legal.title}</h4>
+            <ul>
+              <li><Link href="/privacy-policy">{common.footer.legal.privacyPolicy}</Link></li>
+              <li><Link href="/tos">{common.footer.legal.termsOfService}</Link></li>
+            </ul>
+          </div>
+          <div>
+            <h4>{common.footer.company.title}</h4>
+            <ul>
+              <li><Link href="/blog">{common.footer.company.blog}</Link></li>
+              <li><Link href="/dashboard">{common.footer.company.dashboard}</Link></li>
+            </ul>
+          </div>
+        </div>
+        <div>
+          <p>{common.footer.copyright}</p>
+        </div>
+      </div>
+    </footer>
+  );
+}

apps/webapp/src/components/Header.tsx

@@ -0,0 +1,27 @@
+import Link from "next/link";
+import { getLocale } from "@/libs/locales";
+
+export default function Header() {
+  const { common } = getLocale('en');
+
+  return (
+    <header>
+      {/* TODO: Style this header when implementing in your project */}
+      <div>
+        <div>
+          <div>
+            <Link href="/">{common.header.brand}</Link>
+          </div>
+          <nav>
+            <Link href="/">{common.header.nav.home}</Link>
+            <Link href="/dashboard">{common.header.nav.dashboard}</Link>
+            <Link href="/blog">{common.header.nav.blog}</Link>
+          </nav>
+          <div>
+            <Link href="/login">{common.header.actions.signIn}</Link>
+          </div>
+        </div>
+      </div>
+    </header>
+  );
+}

apps/webapp/src/components/Hero.tsx

@@ -0,0 +1,24 @@
+import Link from "next/link";
+import { getLocale } from "@/libs/locales";
+
+export default function Hero() {
+  const { common } = getLocale('en');
+  
+  return (
+    <section>
+      {/* TODO: Style this hero section when implementing in your project */}
+      <div>
+        <h1>{common.hero.title}</h1>
+        <p>{common.hero.description}</p>
+        <div>
+          <Link href="/dashboard">
+            <button>{common.hero.actions.getStarted}</button>
+          </Link>
+          <Link href="/blog">
+            <button>{common.hero.actions.learnMore}</button>
+          </Link>
+        </div>
+      </div>
+    </section>
+  );
+}

apps/webapp/src/components/Pricing.tsx

@@ -0,0 +1,47 @@
+export default function Pricing() {
+  const plans = [
+    {
+      name: "Open Source",
+      price: "Free",
+      features: [
+        "All boilerplate code",
+        "Docker configurations",
+        "Basic ML setup",
+        "Community support"
+      ]
+    },
+    {
+      name: "Pro",
+      price: "$49/month",
+      features: [
+        "Everything in Open Source",
+        "Advanced configurations",
+        "Priority support",
+        "Custom integrations"
+      ]
+    }
+  ];
+
+  return (
+    <section>
+      {/* TODO: Style this pricing section when implementing in your project */}
+      <div>
+        <h2>Pricing</h2>
+        <div>
+          {plans.map((plan, index) => (
+            <div key={index}>
+              <h3>{plan.name}</h3>
+              <p>{plan.price}</p>
+              <ul>
+                {plan.features.map((feature, featureIndex) => (
+                  <li key={featureIndex}>{feature}</li>
+                ))}
+              </ul>
+              <button>Choose Plan</button>
+            </div>
+          ))}
+        </div>
+      </div>
+    </section>
+  );
+}

apps/webapp/src/components/Testimonials1.tsx

@@ -0,0 +1,25 @@
+import { getLocale } from "@/libs/locales";
+
+export default function Testimonials1() {
+  const { common } = getLocale('en');
+
+  return (
+    <section>
+      {/* TODO: Style this testimonials section when implementing in your project */}
+      <div>
+        <h2>{common.testimonials.title}</h2>
+        <div>
+          {common.testimonials.items.map((testimonial, index) => (
+            <div key={index}>
+              <p>{`"${testimonial.content}"`}</p>
+              <div>
+                <p>{testimonial.name}</p>
+                <p>{testimonial.role}</p>
+              </div>
+            </div>
+          ))}
+        </div>
+      </div>
+    </section>
+  );
+}

apps/webapp/src/libs/locales.ts

@@ -0,0 +1,32 @@
+import commonEn from '@/locales/en/common.json';
+
+// TODO: Add more languages as needed
+const locales = {
+  en: {
+    common: commonEn
+  }
+};
+
+export function getLocale(locale: string = 'en') {
+  return locales[locale as keyof typeof locales] || locales.en;
+}
+
+export function t(key: string, locale: string = 'en') {
+  const translations = getLocale(locale);
+  const keys = key.split('.');
+
+  let value: unknown = translations;
+  for (const k of keys) {
+    if (typeof value !== 'object' || value === null || !(k in value)) {
+      return key;
+    }
+
+    value = (value as Record<string, unknown>)[k];
+  }
+
+  if (typeof value === 'string' || typeof value === 'number') {
+    return String(value);
+  }
+
+  return key;
+}

apps/webapp/src/locales/en/common.json

@@ -0,0 +1,85 @@
+{
+  "header": {
+    "brand": "UltiPlate",
+    "nav": {
+      "home": "Home",
+      "dashboard": "Dashboard",
+      "blog": "Blog"
+    },
+    "actions": {
+      "signIn": "Sign In"
+    }
+  },
+  "footer": {
+    "brand": "UltiPlate",
+    "description": "Ultimate boilerplate for any project",
+    "legal": {
+      "title": "Legal",
+      "privacyPolicy": "Privacy Policy",
+      "termsOfService": "Terms of Service"
+    },
+    "company": {
+      "title": "Company",
+      "blog": "Blog",
+      "dashboard": "Dashboard"
+    },
+    "copyright": "© 2024 UltiPlate. All rights reserved."
+  },
+  "hero": {
+    "title": "Welcome to UltiPlate",
+    "description": "The ultimate boilerplate for any project - from web apps to ML projects, all deployable with Docker.",
+    "actions": {
+      "getStarted": "Get Started",
+      "learnMore": "Learn More"
+    }
+  },
+  "features": {
+    "title": "Features",
+    "items": [
+      {
+        "title": "Docker Ready",
+        "description": "Everything containerized and ready to deploy"
+      },
+      {
+        "title": "ML Support", 
+        "description": "Built-in machine learning project structure"
+      },
+      {
+        "title": "Multiple Backends",
+        "description": "FastAPI, Flask, and more backend options"
+      },
+      {
+        "title": "Centralized Logging",
+        "description": "Loki-based logging across all services"
+      },
+      {
+        "title": "Database Ready",
+        "description": "Redis, MinIO, and database integrations"
+      },
+      {
+        "title": "Web Apps",
+        "description": "Next.js and Streamlit app templates"
+      }
+    ]
+  },
+  "testimonials": {
+    "title": "What People Say",
+    "items": [
+      {
+        "name": "Alex Developer",
+        "role": "Full Stack Developer",
+        "content": "UltiPlate saved me weeks of setup time. Everything just works out of the box."
+      },
+      {
+        "name": "Sarah ML Engineer",
+        "role": "ML Engineer",
+        "content": "The ML project structure is perfect. From notebooks to production in minutes."
+      },
+      {
+        "name": "Mike DevOps",
+        "role": "DevOps Engineer",
+        "content": "Docker integration is seamless. Deploy anywhere with confidence."
+      }
+    ]
+  }
+}

apps/webapp/src/utils/supabase/client.ts

@@ -0,0 +1,8 @@
+import { createBrowserClient } from '@supabase/ssr'
+
+export function createClient() {
+  return createBrowserClient(
+    process.env.NEXT_PUBLIC_SUPABASE_URL!,
+    process.env.NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY!
+  )
+}

apps/webapp/src/utils/supabase/middleware.ts

@@ -0,0 +1,66 @@
+import { createServerClient } from '@supabase/ssr'
+import { NextResponse, type NextRequest } from 'next/server'
+
+export async function updateSession(request: NextRequest) {
+  let supabaseResponse = NextResponse.next({
+    request,
+  })
+
+  const supabase = createServerClient(
+    process.env.NEXT_PUBLIC_SUPABASE_URL!,
+    process.env.NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY!,
+    {
+      cookies: {
+        getAll() {
+          return request.cookies.getAll()
+        },
+        setAll(cookiesToSet) {
+          cookiesToSet.forEach(({ name, value }) => request.cookies.set(name, value))
+          supabaseResponse = NextResponse.next({
+            request,
+          })
+          cookiesToSet.forEach(({ name, value, options }) =>
+            supabaseResponse.cookies.set(name, value, options)
+          )
+        },
+      },
+    }
+  )
+
+  // Do not run code between createServerClient and
+  // supabase.auth.getUser(). A simple mistake could make it very hard to debug
+  // issues with users being randomly logged out.
+
+  // IMPORTANT: DO NOT REMOVE auth.getUser()
+
+  const {
+    data: { user },
+  } = await supabase.auth.getUser()
+
+  if (
+    !user &&
+    !request.nextUrl.pathname.startsWith('/login') &&
+    !request.nextUrl.pathname.startsWith('/auth') &&
+    !request.nextUrl.pathname.startsWith('/error')
+  ) {
+    // no user, potentially respond by redirecting the user to the login page
+    const url = request.nextUrl.clone()
+    url.pathname = '/login'
+    return NextResponse.redirect(url)
+  }
+
+  // IMPORTANT: You *must* return the supabaseResponse object as it is.
+  // If you're creating a new response object with NextResponse.next() make sure to:
+  // 1. Pass the request in it, like so:
+  //    const myNewResponse = NextResponse.next({ request })
+  // 2. Copy over the cookies, like so:
+  //    myNewResponse.cookies.setAll(supabaseResponse.cookies.getAll())
+  // 3. Change the myNewResponse object to fit your needs, but avoid changing
+  //    the cookies!
+  // 4. Finally:
+  //    return myNewResponse
+  // If this is not done, you may be causing the browser and server to go out
+  // of sync and terminate the user's session prematurely!
+
+  return supabaseResponse
+}

apps/webapp/src/utils/supabase/server.ts

@@ -0,0 +1,29 @@
+import { createServerClient } from '@supabase/ssr'
+import { cookies } from 'next/headers'
+
+export async function createClient() {
+  const cookieStore = await cookies()
+
+  return createServerClient(
+    process.env.NEXT_PUBLIC_SUPABASE_URL!,
+    process.env.NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY!,
+    {
+      cookies: {
+        getAll() {
+          return cookieStore.getAll()
+        },
+        setAll(cookiesToSet) {
+          try {
+            cookiesToSet.forEach(({ name, value, options }) =>
+              cookieStore.set(name, value, options)
+            )
+          } catch {
+            // The `setAll` method was called from a Server Component.
+            // This can be ignored if you have middleware refreshing
+            // user sessions.
+          }
+        },
+      },
+    }
+  )
+}

apps/webapp/tsconfig.json

@@ -0,0 +1,27 @@
+{
+  "compilerOptions": {
+    "target": "ES2017",
+    "lib": ["dom", "dom.iterable", "esnext"],
+    "allowJs": true,
+    "skipLibCheck": true,
+    "strict": true,
+    "noEmit": true,
+    "esModuleInterop": true,
+    "module": "esnext",
+    "moduleResolution": "bundler",
+    "resolveJsonModule": true,
+    "isolatedModules": true,
+    "jsx": "preserve",
+    "incremental": true,
+    "plugins": [
+      {
+        "name": "next"
+      }
+    ],
+    "paths": {
+      "@/*": ["./src/*"]
+    }
+  },
+  "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
+  "exclude": ["node_modules"]
+}

apps/worker/project.json

@@ -0,0 +1,40 @@
+{
+  "name": "worker",
+  "root": "apps/worker",
+  "sourceRoot": "apps/worker",
+  "projectType": "application",
+  "implicitDependencies": ["alveslib"],
+  "targets": {
+    "dev": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "apps/worker",
+        "command": "celery -A worker:app worker --loglevel=info"
+      }
+    },
+    "build": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "python3.12 -m compileall apps/worker"
+      }
+    },
+    "lint": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/ruff check apps/worker"
+      }
+    },
+    "typecheck": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/mypy apps/worker"
+      }
+    },
+    "test": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": ".venv/bin/pytest apps/worker -v"
+      }
+    }
+  }
+}

apps/worker/worker.py

@@ -0,0 +1,23 @@
+import os
+import time
+from celery import Celery
+from dotenv import load_dotenv
+load_dotenv()
+
+# Redis connection
+redis_url = os.getenv("REDIS_URL", "redis://localhost:6379")
+app = Celery('worker', broker=redis_url, backend=redis_url)
+
+@app.task
+def simple_task(message):
+    """A simple task that processes a message and returns a result"""
+    time.sleep(2)  # Simulate some work
+    return f"Processed: {message}"
+
+@app.task
+def add_numbers(x, y):
+    """Simple math task"""
+    return x + y
+
+if __name__ == '__main__':
+    app.start()

bun.lock

@@ -0,0 +1,275 @@
+{
+  "lockfileVersion": 1,
+  "configVersion": 1,
+  "workspaces": {
+    "": {
+      "name": "ultiplate",
+      "devDependencies": {
+        "nx": "^20.8.2",
+      },
+    },
+  },
+  "packages": {
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+    "jsonc-parser": ["jsonc-parser@3.2.0", "", {}, "sha512-gfFQZrcTc8CnKXp6Y4/CBT3fTc0OVuDofpre4aEeEpSBPV5X5v4+Vmx+8snU7RLPrNHPKSgLxGo9YuQzz20o+w=="],
+
+    "lines-and-columns": ["lines-and-columns@2.0.3", "", {}, "sha512-cNOjgCnLB+FnvWWtyRTzmB3POJ+cXxTA81LoW7u8JdmhfXzriropYwpjShnz1QLLWsQwY7nIxoDmcPTwphDK9w=="],
+
+    "log-symbols": ["log-symbols@4.1.0", "", { "dependencies": { "chalk": "^4.1.0", "is-unicode-supported": "^0.1.0" } }, "sha512-8XPvpAA8uyhfteu8pIvQxpJZ7SYYdpUivZpGy6sFsBuKRY/7rQGavedeB8aK+Zkyq6upMFVL/9AW6vOYzfRyLg=="],
+
+    "math-intrinsics": ["math-intrinsics@1.1.0", "", {}, "sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g=="],
+
+    "mime-db": ["mime-db@1.52.0", "", {}, "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg=="],
+
+    "mime-types": ["mime-types@2.1.35", "", { "dependencies": { "mime-db": "1.52.0" } }, "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw=="],
+
+    "mimic-fn": ["mimic-fn@2.1.0", "", {}, "sha512-OqbOk5oEQeAZ8WXWydlu9HJjz9WVdEIvamMCcXmuqUYjTknH/sqsWvhQ3vgwKFRR1HpjvNBKQ37nbJgYzGqGcg=="],
+
+    "minimatch": ["minimatch@9.0.3", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-RHiac9mvaRw0x3AYRgDC1CxAP7HTcNrrECeA8YYJeWnpo+2Q5CegtZjaotWTWxDG3UeGA1coE05iH1mPjT/2mg=="],
+
+    "minimist": ["minimist@1.2.8", "", {}, "sha512-2yyAR8qBkN3YuheJanUpWC5U3bb5osDywNB8RzDVlDwDHbocAJveqqj1u8+SVD7jkWT4yvsHCpWqqWqAxb0zCA=="],
+
+    "node-machine-id": ["node-machine-id@1.1.12", "", {}, "sha512-QNABxbrPa3qEIfrE6GOJ7BYIuignnJw7iQ2YPbc3Nla1HzRJjXzZOiikfF8m7eAMfichLt3M4VgLOetqgDmgGQ=="],
+
+    "npm-run-path": ["npm-run-path@4.0.1", "", { "dependencies": { "path-key": "^3.0.0" } }, "sha512-S48WzZW777zhNIrn7gxOlISNAqi9ZC/uQFnRdbeIHhZhCA6UqpkOT8T1G7BvfdgP4Er8gF4sUbaS0i7QvIfCWw=="],
+
+    "nx": ["nx@20.8.4", "", { "dependencies": { "@napi-rs/wasm-runtime": "0.2.4", "@yarnpkg/lockfile": "^1.1.0", "@yarnpkg/parsers": "3.0.2", "@zkochan/js-yaml": "0.0.7", "axios": "^1.8.3", "chalk": "^4.1.0", "cli-cursor": "3.1.0", "cli-spinners": "2.6.1", "cliui": "^8.0.1", "dotenv": "~16.4.5", "dotenv-expand": "~11.0.6", "enquirer": "~2.3.6", "figures": "3.2.0", "flat": "^5.0.2", "front-matter": "^4.0.2", "ignore": "^5.0.4", "jest-diff": "^29.4.1", "jsonc-parser": "3.2.0", "lines-and-columns": "2.0.3", "minimatch": "9.0.3", "node-machine-id": "1.1.12", "npm-run-path": "^4.0.1", "open": "^8.4.0", "ora": "5.3.0", "resolve.exports": "2.0.3", "semver": "^7.5.3", "string-width": "^4.2.3", "tar-stream": "~2.2.0", "tmp": "~0.2.1", "tsconfig-paths": "^4.1.2", "tslib": "^2.3.0", "yaml": "^2.6.0", "yargs": "^17.6.2", "yargs-parser": "21.1.1" }, "optionalDependencies": { "@nx/nx-darwin-arm64": "20.8.4", "@nx/nx-darwin-x64": "20.8.4", "@nx/nx-freebsd-x64": "20.8.4", "@nx/nx-linux-arm-gnueabihf": "20.8.4", "@nx/nx-linux-arm64-gnu": "20.8.4", "@nx/nx-linux-arm64-musl": "20.8.4", "@nx/nx-linux-x64-gnu": "20.8.4", "@nx/nx-linux-x64-musl": "20.8.4", "@nx/nx-win32-arm64-msvc": "20.8.4", "@nx/nx-win32-x64-msvc": "20.8.4" }, "peerDependencies": { "@swc-node/register": "^1.8.0", "@swc/core": "^1.3.85" }, "optionalPeers": ["@swc-node/register", "@swc/core"], "bin": { "nx": "bin/nx.js", "nx-cloud": "bin/nx-cloud.js" } }, "sha512-/++x0OM3/UTmDR+wmPeV13tSxeTr+QGzj3flgtH9DiOPmQnn2CjHWAMZiOhcSh/hHoE/V3ySL4757InQUsVtjQ=="],
+
+    "once": ["once@1.4.0", "", { "dependencies": { "wrappy": "1" } }, "sha512-lNaJgI+2Q5URQBkccEKHTQOPaXdUxnZZElQTZY0MFUAuaEqe1E+Nyvgdz/aIyNi6Z9MzO5dv1H8n58/GELp3+w=="],
+
+    "onetime": ["onetime@5.1.2", "", { "dependencies": { "mimic-fn": "^2.1.0" } }, "sha512-kbpaSSGJTWdAY5KPVeMOKXSrPtr8C8C7wodJbcsd51jRnmD+GZu8Y0VoU6Dm5Z4vWr0Ig/1NKuWRKf7j5aaYSg=="],
+
+    "open": ["open@8.4.2", "", { "dependencies": { "define-lazy-prop": "^2.0.0", "is-docker": "^2.1.1", "is-wsl": "^2.2.0" } }, "sha512-7x81NCL719oNbsq/3mh+hVrAWmFuEYUqrq/Iw3kUzH8ReypT9QQ0BLoJS7/G9k6N81XjW4qHWtjWwe/9eLy1EQ=="],
+
+    "ora": ["ora@5.3.0", "", { "dependencies": { "bl": "^4.0.3", "chalk": "^4.1.0", "cli-cursor": "^3.1.0", "cli-spinners": "^2.5.0", "is-interactive": "^1.0.0", "log-symbols": "^4.0.0", "strip-ansi": "^6.0.0", "wcwidth": "^1.0.1" } }, "sha512-zAKMgGXUim0Jyd6CXK9lraBnD3H5yPGBPPOkC23a2BG6hsm4Zu6OQSjQuEtV0BHDf4aKHcUFvJiGRrFuW3MG8g=="],
+
+    "path-key": ["path-key@3.1.1", "", {}, "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q=="],
+
+    "pretty-format": ["pretty-format@29.7.0", "", { "dependencies": { "@jest/schemas": "^29.6.3", "ansi-styles": "^5.0.0", "react-is": "^18.0.0" } }, "sha512-Pdlw/oPxN+aXdmM9R00JVC9WVFoCLTKJvDVLgmJ+qAffBMxsV85l/Lu7sNx4zSzPyoL2euImuEwHhOXdEgNFZQ=="],
+
+    "proxy-from-env": ["proxy-from-env@1.1.0", "", {}, "sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg=="],
+
+    "react-is": ["react-is@18.3.1", "", {}, "sha512-/LLMVyas0ljjAtoYiPqYiL8VWXzUUdThrmU5+n20DZv+a+ClRoevUzw5JxU+Ieh5/c87ytoTBV9G1FiKfNJdmg=="],
+
+    "readable-stream": ["readable-stream@3.6.2", "", { "dependencies": { "inherits": "^2.0.3", "string_decoder": "^1.1.1", "util-deprecate": "^1.0.1" } }, "sha512-9u/sniCrY3D5WdsERHzHE4G2YCXqoG5FTHUiCC4SIbr6XcLZBY05ya9EKjYek9O5xOAwjGq+1JdGBAS7Q9ScoA=="],
+
+    "require-directory": ["require-directory@2.1.1", "", {}, "sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q=="],
+
+    "resolve.exports": ["resolve.exports@2.0.3", "", {}, "sha512-OcXjMsGdhL4XnbShKpAcSqPMzQoYkYyhbEaeSko47MjRP9NfEQMhZkXL1DoFlt9LWQn4YttrdnV6X2OiyzBi+A=="],
+
+    "restore-cursor": ["restore-cursor@3.1.0", "", { "dependencies": { "onetime": "^5.1.0", "signal-exit": "^3.0.2" } }, "sha512-l+sSefzHpj5qimhFSE5a8nufZYAM3sBSVMAPtYkmC+4EH2anSGaEMXSD0izRQbu9nfyQ9y5JrVmp7E8oZrUjvA=="],
+
+    "safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
+
+    "semver": ["semver@7.7.4", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA=="],
+
+    "signal-exit": ["signal-exit@3.0.7", "", {}, "sha512-wnD2ZE+l+SPC/uoS0vXeE9L1+0wuaMqKlfz9AMUo38JsyLSBWSFcHR1Rri62LZc12vLr1gb3jl7iwQhgwpAbGQ=="],
+
+    "sprintf-js": ["sprintf-js@1.0.3", "", {}, "sha512-D9cPgkvLlV3t3IzL0D0YLvGA9Ahk4PcvVwUbN0dSGr1aP0Nrt4AEnTUbuGvquEC0mA64Gqt1fzirlRs5ibXx8g=="],
+
+    "string-width": ["string-width@4.2.3", "", { "dependencies": { "emoji-regex": "^8.0.0", "is-fullwidth-code-point": "^3.0.0", "strip-ansi": "^6.0.1" } }, "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g=="],
+
+    "string_decoder": ["string_decoder@1.3.0", "", { "dependencies": { "safe-buffer": "~5.2.0" } }, "sha512-hkRX8U1WjJFd8LsDJ2yQ/wWWxaopEsABU1XfkM8A+j0+85JAGppt16cr1Whg6KIbb4okU6Mql6BOj+uup/wKeA=="],
+
+    "strip-ansi": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
+
+    "strip-bom": ["strip-bom@3.0.0", "", {}, "sha512-vavAMRXOgBVNF6nyEEmL3DBK19iRpDcoIwW+swQ+CbGiu7lju6t+JklA1MHweoWtadgt4ISVUsXLyDq34ddcwA=="],
+
+    "supports-color": ["supports-color@7.2.0", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw=="],
+
+    "tar-stream": ["tar-stream@2.2.0", "", { "dependencies": { "bl": "^4.0.3", "end-of-stream": "^1.4.1", "fs-constants": "^1.0.0", "inherits": "^2.0.3", "readable-stream": "^3.1.1" } }, "sha512-ujeqbceABgwMZxEJnk2HDY2DlnUZ+9oEcb1KzTVfYHio0UE6dG71n60d8D2I4qNvleWrrXpmjpt7vZeF1LnMZQ=="],
+
+    "tmp": ["tmp@0.2.5", "", {}, "sha512-voyz6MApa1rQGUxT3E+BK7/ROe8itEx7vD8/HEvt4xwXucvQ5G5oeEiHkmHZJuBO21RpOf+YYm9MOivj709jow=="],
+
+    "tsconfig-paths": ["tsconfig-paths@4.2.0", "", { "dependencies": { "json5": "^2.2.2", "minimist": "^1.2.6", "strip-bom": "^3.0.0" } }, "sha512-NoZ4roiN7LnbKn9QqE1amc9DJfzvZXxF4xDavcOWt1BPkdx+m+0gJuPM+S0vCe7zTJMYUP0R8pO2XMr+Y8oLIg=="],
+
+    "tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
+
+    "util-deprecate": ["util-deprecate@1.0.2", "", {}, "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw=="],
+
+    "wcwidth": ["wcwidth@1.0.1", "", { "dependencies": { "defaults": "^1.0.3" } }, "sha512-XHPEwS0q6TaxcvG85+8EYkbiCux2XtWG2mkc47Ng2A77BQu9+DqIOJldST4HgPkuea7dvKSj5VgX3P1d4rW8Tg=="],
+
+    "wrap-ansi": ["wrap-ansi@7.0.0", "", { "dependencies": { "ansi-styles": "^4.0.0", "string-width": "^4.1.0", "strip-ansi": "^6.0.0" } }, "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q=="],
+
+    "wrappy": ["wrappy@1.0.2", "", {}, "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ=="],
+
+    "y18n": ["y18n@5.0.8", "", {}, "sha512-0pfFzegeDWJHJIAmTLRP2DwHjdF5s7jo9tuztdQxAhINCdvS+3nGINqPd00AphqJR/0LhANUS6/+7SCb98YOfA=="],
+
+    "yaml": ["yaml@2.8.2", "", { "bin": { "yaml": "bin.mjs" } }, "sha512-mplynKqc1C2hTVYxd0PU2xQAc22TI1vShAYGksCCfxbn/dFwnHTNi1bvYsBTkhdUNtGIf5xNOg938rrSSYvS9A=="],
+
+    "yargs": ["yargs@17.7.2", "", { "dependencies": { "cliui": "^8.0.1", "escalade": "^3.1.1", "get-caller-file": "^2.0.5", "require-directory": "^2.1.1", "string-width": "^4.2.3", "y18n": "^5.0.5", "yargs-parser": "^21.1.1" } }, "sha512-7dSzzRQ++CKnNI/krKnYRV7JKKPUXMEh61soaHKg9mrWEhzFWhFnxPxGl+69cD1Ou63C13NUPCnmIcrvqCuM6w=="],
+
+    "yargs-parser": ["yargs-parser@21.1.1", "", {}, "sha512-tVpsJW7DdjecAiFpbIB1e3qxIQsE6NoPc5/eTdrbbIC4h0LVsWhnoa3g+m2HclBIujHzsxZ4VJVA+GUuc2/LBw=="],
+
+    "js-yaml/argparse": ["argparse@1.0.10", "", { "dependencies": { "sprintf-js": "~1.0.2" } }, "sha512-o5Roy6tNG4SL/FOkCAN6RzjiakZS25RLYFrcMttJqbdd8BWrnA+fGz57iN5Pb06pvBGvl5gQ0B48dJlslXvoTg=="],
+
+    "pretty-format/ansi-styles": ["ansi-styles@5.2.0", "", {}, "sha512-Cxwpt2SfTzTtXcfOlzGEee8O+c+MmUgGrNiBcXnuWxuFJHe6a5Hz7qwhwe5OgaSYI0IJvkLqWX1ASG+cJOkEiA=="],
+  }
+}

docker-compose.yml

@@ -0,0 +1,162 @@
+services:
+  redis:
+    container_name: "${NAME}-redis"
+    image: redis:7-alpine
+    ports:
+      - "${REDIS_PORT}:6379"
+    volumes:
+      - redis_data:/data
+    restart: unless-stopped
+
+  ml-inference:
+    container_name: "${NAME}-mlinfer"
+    build:
+      context: ./
+      dockerfile: ./docker/ml.Dockerfile
+    ports:
+      - "8200:8000"
+    environment:
+      - ML_LATEST_WEIGHTS_PATH=/app/models/weights
+      - PYTHONPATH=/app
+    volumes:
+      - ./ml/models:/app/models
+      - ./.env:/app/.env
+    depends_on:
+      - redis
+    restart: unless-stopped
+
+  worker:
+    container_name: "${NAME}-worker"
+    build:
+      context: ./
+      dockerfile: ./docker/worker.Dockerfile
+    environment:
+      - REDIS_URL=redis://redis:6379
+      - PYTHONPATH=/app
+    volumes:
+      - ./.env:/app/.env
+    depends_on:
+      - redis
+    restart: unless-stopped
+
+  minio:
+    image: minio/minio:latest
+    container_name: "${NAME}-minio"
+    profiles: ["minio"]
+    ports:
+      - "9900:9000"   # API endpoint
+      - "9901:9001"   # Web console
+    environment:
+      MINIO_ROOT_USER: minioadmin
+      MINIO_ROOT_PASSWORD: minioadmin
+    volumes:
+      - minio_data:/data
+    command: server /data --console-address ":9001"
+    restart: unless-stopped
+
+  create-bucket:
+    image: minio/mc
+    container_name: "${NAME}-create-bucket"
+    profiles: ["minio"]
+    depends_on:
+      - minio
+    entrypoint: >
+      /bin/sh -c "
+      sleep 5;
+      mc alias set myminio http://minio:9000 minioadmin minioadmin;
+      mc mb myminio/${NAME:-app} --ignore-existing;
+      exit 0;
+      "
+
+  tensorboard:
+    image: tensorflow/tensorflow:latest
+    container_name: "${NAME}-tensorboard"
+    profiles: ["tensorboard"]
+    ports:
+      - "6006:6006"
+    volumes:
+      - ./ml/tensorboard:/logs
+    command: tensorboard --logdir=/logs --host=0.0.0.0 --port=6006
+    restart: unless-stopped
+
+  mlflow:
+    image: python:3.12-slim
+    container_name: "${NAME}-mlflow"
+    profiles: ["mlflow"]
+    ports:
+      - "5000:5000"
+    volumes:
+      - mlflow_data:/mlflow
+    command: >
+      /bin/sh -c "
+      pip install --no-cache-dir mlflow &&
+      mlflow server
+      --host 0.0.0.0
+      --port 5000
+      --backend-store-uri sqlite:////mlflow/mlflow.db
+      --default-artifact-root /mlflow/artifacts
+      "
+    restart: unless-stopped
+
+  # Logging Infrastructure - Minimal Setup
+  loki:
+    image: grafana/loki:2.9.0
+    container_name: "${NAME}-loki"
+    profiles: ["logging"]
+    ports:
+      - "${LOKI_PORT}:3100"
+    volumes:
+      - loki_data:/loki
+    restart: unless-stopped
+
+  grafana:
+    image: grafana/grafana:10.2.0
+    container_name: "${NAME}-grafana"
+    profiles: ["logging"]
+    ports:
+      - "${GRAFANA_PORT}:3000"
+    environment:
+      - GF_SECURITY_ADMIN_PASSWORD=admin
+    volumes:
+      - grafana_data:/var/lib/grafana
+    restart: unless-stopped
+
+  # Database Services
+  postgres:
+    image: postgres:15-alpine
+    container_name: "${NAME}-postgres"
+    profiles: ["database", "postgres"]
+    ports:
+      - "${POSTGRES_PORT:-5432}:5432"
+    environment:
+      POSTGRES_DB: ${POSTGRES_DB:-app}
+      POSTGRES_USER: ${POSTGRES_USER:-postgres}
+      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-postgres}
+    volumes:
+      - postgres_data:/var/lib/postgresql/data
+      # place .sql files in ./database/ to auto-run on first start
+      - ./database/:/docker-entrypoint-initdb.d/:ro
+    restart: unless-stopped
+
+  mongodb:
+    image: mongo:7-jammy
+    container_name: "${NAME}-mongodb"
+    profiles: ["database", "mongodb"]
+    ports:
+      - "${MONGO_PORT:-27017}:27017"
+    environment:
+      MONGO_INITDB_ROOT_USERNAME: ${MONGO_USER:-admin}
+      MONGO_INITDB_ROOT_PASSWORD: ${MONGO_PASSWORD:-admin123}
+      MONGO_INITDB_DATABASE: ${MONGO_DB:-app}
+    volumes:
+      - mongodb_data:/data/db
+    restart: unless-stopped
+
+volumes:
+  redis_data:
+  minio_data:
+  loki_data:
+  grafana_data:
+  postgres_data:
+  mongodb_data:
+  mlflow_data:

docker/ml.Dockerfile

@@ -0,0 +1,38 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+# System deps - layer rarely changes
+RUN apt-get update && apt-get install -y \
+    gcc \
+    g++ \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install external dependencies only - layer cached until pyproject.toml changes.
+# Stub files satisfy setuptools' package discovery without real source,
+# so external deps are downloaded once and reused across source-only rebuilds.
+COPY pyproject.toml ./
+RUN touch README.md \
+    && mkdir -p alveslib && touch alveslib/__init__.py \
+    && pip install --no-cache-dir . \
+    && rm -rf alveslib README.md
+
+# Copy local library and reinstall it without re-downloading external deps
+COPY alveslib/ ./alveslib/
+RUN pip install --no-cache-dir --no-deps .
+
+# Copy application source last - most frequently changed
+COPY ml/ ./
+COPY src/ ./src/
+
+RUN mkdir -p /app/models/weights
+
+HEALTHCHECK --interval=30s --timeout=30s --start-period=60s --retries=3 \
+    CMD python -c "import requests; requests.get('http://localhost:8000/health').raise_for_status()" || exit 1
+
+EXPOSE 8000
+
+RUN useradd --create-home --shell /bin/bash app
+RUN chown -R app:app /app
+USER app
+CMD ["uvicorn", "inference:app", "--host", "0.0.0.0", "--port", "8000"]

docker/worker.Dockerfile

@@ -0,0 +1,34 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+# System deps - layer rarely changes
+RUN apt-get update && apt-get install -y \
+    gcc \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install external dependencies only - layer cached until pyproject.toml changes.
+# Stub files satisfy setuptools' package discovery without real source,
+# so external deps are downloaded once and reused across source-only rebuilds.
+COPY pyproject.toml ./
+RUN touch README.md \
+    && mkdir -p alveslib && touch alveslib/__init__.py \
+    && pip install --no-cache-dir . \
+    && rm -rf alveslib README.md
+
+# Copy local library and reinstall it without re-downloading external deps
+COPY alveslib/ ./alveslib/
+RUN pip install --no-cache-dir --no-deps .
+
+# Copy application source last - most frequently changed
+RUN mkdir -p ./worker/
+COPY apps/worker/ ./worker/
+COPY src/ ./src/
+
+HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
+    CMD python -c "import redis; r=redis.from_url('redis://redis:6379'); r.ping()" || exit 1
+
+RUN useradd --create-home --shell /bin/bash app
+RUN chown -R app:app /app
+USER app
+CMD ["celery", "-A", "worker.worker:app", "worker", "--loglevel=info"]

ml/configs/data/default.yaml

@@ -0,0 +1,6 @@
+dataset_name: synthetic_classification
+output_dir: ml/data/processed
+train_samples: 2048
+input_dim: 16
+num_classes: 3
+seed: 42

ml/configs/train/default.yaml

@@ -0,0 +1,10 @@
+input_dim: 16
+hidden_dim: 64
+num_classes: 3
+learning_rate: 0.001
+batch_size: 64
+epochs: 5
+log_every_n_steps: 20
+seed: 42
+tensorboard_dir: ml/tensorboard
+weights_output: ml/models/weights/model.pt

ml/data/README.md

@@ -0,0 +1,5 @@
+# Data
+
+Some thoughts on processing data: In a lot of cases you will get data not in an s3 bucket or anything glamarous and for doing anything in terms of modelling you need the data locally but then when you maybe have a 1TB dataset you want 10GB locally and then you upload to a GPU rich server and there you will want all of teh data. How can you managed this data well? What are best practices?
+
+Huggingface lets you upload up to 300 gigs of data into a dataset.

ml/data/etl.py

@@ -0,0 +1,52 @@
+import argparse
+import json
+from pathlib import Path
+
+import torch
+import yaml
+
+
+def build_dataset(
+    train_samples: int, input_dim: int, num_classes: int, seed: int
+) -> dict[str, torch.Tensor]:
+    generator = torch.Generator().manual_seed(seed)
+    features = torch.randn(train_samples, input_dim, generator=generator)
+    labels = torch.randint(0, num_classes, (train_samples,), generator=generator)
+    return {"features": features, "labels": labels}
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Build a synthetic training dataset")
+    parser.add_argument("--config", default="ml/configs/data/default.yaml")
+    parser.add_argument("--output", default="ml/data/processed")
+    args = parser.parse_args()
+
+    with open(args.config, "r", encoding="utf-8") as f:
+        cfg = yaml.safe_load(f)
+
+    output_dir = Path(args.output)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    dataset = build_dataset(
+        train_samples=int(cfg["train_samples"]),
+        input_dim=int(cfg["input_dim"]),
+        num_classes=int(cfg["num_classes"]),
+        seed=int(cfg["seed"]),
+    )
+    dataset_path = output_dir / "dataset.pt"
+    torch.save(dataset, dataset_path)
+
+    metadata = {
+        "dataset_name": cfg["dataset_name"],
+        "train_samples": int(cfg["train_samples"]),
+        "input_dim": int(cfg["input_dim"]),
+        "num_classes": int(cfg["num_classes"]),
+        "seed": int(cfg["seed"]),
+        "dataset_path": str(dataset_path),
+    }
+    with open(output_dir / "metadata.json", "w", encoding="utf-8") as f:
+        json.dump(metadata, f, indent=2)
+
+
+if __name__ == "__main__":
+    main()

ml/data/processed/metadata.json

@@ -0,0 +1,8 @@
+{
+  "dataset_name": "synthetic_classification",
+  "train_samples": 2048,
+  "input_dim": 16,
+  "num_classes": 3,
+  "seed": 42,
+  "dataset_path": "ml/data/processed/dataset.pt"
+}

ml/inference.py

@@ -0,0 +1,36 @@
+import os
+import torch
+import torch.nn as nn
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+# TODO: Import model when ready
+from models import * # TODO: SPECIFY
+
+class InputData(BaseModel):
+    pass
+
+
+weights_path = os.getenv("ML_LATEST_WEIGHTS_PATH")
+if weights_path is None:
+    raise RuntimeError("ML_LATEST_WEIGHTS_PATH not set")
+
+
+# FastAPI app
+app = FastAPI(title="ML Inference API", version="1.0.0")
+
+@app.get("/health")
+def health_check():
+    return {"status": "healthy", "service": "ml-inference"}
+
+@app.post("/predict")
+def predict(data: InputData):
+
+    #TODO: x = torch.tensor([data.features], dtype=torch.float32)
+
+    with torch.no_grad():
+
+        #TODO: y = model(x)
+
+        y=torch.tensor(0)
+    return {"prediction": y.tolist()}

ml/models/arch.py

@@ -0,0 +1,15 @@
+import torch
+import torch.nn as nn
+
+
+class Model(nn.Module):
+    def __init__(self, input_dim: int, hidden_dim: int, num_classes: int) -> None:
+        super().__init__()
+        self.net = nn.Sequential(
+            nn.Linear(input_dim, hidden_dim),
+            nn.ReLU(),
+            nn.Linear(hidden_dim, num_classes),
+        )
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        return self.net(x)

ml/models/train.py

@@ -0,0 +1,98 @@
+import argparse
+from pathlib import Path
+
+import torch
+import torch.nn as nn
+import yaml
+from torch.utils.data import DataLoader, TensorDataset
+from torch.utils.tensorboard import SummaryWriter
+
+from alveslib import get_logger
+from ml.models.arch import Model
+
+logger = get_logger("ml-train")
+
+
+class Trainer:
+    def __init__(
+        self,
+        model: nn.Module,
+        train_loader: DataLoader,
+        learning_rate: float,
+        log_dir: str,
+        log_every_n_steps: int,
+    ) -> None:
+        self.model = model
+        self.train_loader = train_loader
+        self.optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)
+        self.criterion = nn.CrossEntropyLoss()
+        self.writer = SummaryWriter(log_dir)
+        self.step = 0
+        self.log_every_n_steps = log_every_n_steps
+
+    def train_epoch(self) -> float:
+        self.model.train()
+        total_loss = 0.0
+        for batch_idx, (features, target) in enumerate(self.train_loader):
+            self.optimizer.zero_grad()
+            output = self.model(features)
+            loss = self.criterion(output, target)
+            loss.backward()
+            self.optimizer.step()
+
+            total_loss += loss.item()
+            if batch_idx % self.log_every_n_steps == 0:
+                self.writer.add_scalar("Loss/TrainStep", loss.item(), self.step)
+            self.step += 1
+
+        return total_loss / max(len(self.train_loader), 1)
+
+    def train(self, epochs: int) -> None:
+        for epoch in range(epochs):
+            avg_loss = self.train_epoch()
+            self.writer.add_scalar("Loss/TrainEpoch", avg_loss, epoch)
+            logger.info(f"epoch={epoch + 1}/{epochs} avg_loss={avg_loss:.5f}")
+        self.writer.close()
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Train a baseline model")
+    parser.add_argument("--config", default="ml/configs/train/default.yaml")
+    parser.add_argument("--dataset", default="ml/data/processed/dataset.pt")
+    parser.add_argument("--weights", default=None)
+    args = parser.parse_args()
+
+    with open(args.config, "r", encoding="utf-8") as f:
+        cfg = yaml.safe_load(f)
+
+    torch.manual_seed(int(cfg["seed"]))
+
+    dataset_blob = torch.load(args.dataset, map_location="cpu")
+    dataset = TensorDataset(dataset_blob["features"], dataset_blob["labels"])
+    train_loader = DataLoader(dataset, batch_size=int(cfg["batch_size"]), shuffle=True)
+
+    model = Model(
+        input_dim=int(cfg["input_dim"]),
+        hidden_dim=int(cfg["hidden_dim"]),
+        num_classes=int(cfg["num_classes"]),
+    )
+    trainer = Trainer(
+        model=model,
+        train_loader=train_loader,
+        learning_rate=float(cfg["learning_rate"]),
+        log_dir=str(cfg["tensorboard_dir"]),
+        log_every_n_steps=int(cfg["log_every_n_steps"]),
+    )
+    trainer.train(epochs=int(cfg["epochs"]))
+
+    weights_target = args.weights or cfg.get(
+        "weights_output", "ml/models/weights/model.pt"
+    )
+    weights_path = Path(weights_target)
+    weights_path.parent.mkdir(parents=True, exist_ok=True)
+    torch.save(model.state_dict(), weights_path)
+    logger.info(f"saved_weights={weights_path}")
+
+
+if __name__ == "__main__":
+    main()

ml/project.json

@@ -0,0 +1,70 @@
+{
+  "name": "ml",
+  "root": "ml",
+  "sourceRoot": "ml",
+  "projectType": "application",
+  "implicitDependencies": ["alveslib"],
+  "targets": {
+    "dev": {
+      "executor": "nx:run-commands",
+      "options": {
+        "cwd": "ml",
+        "command": "uvicorn inference:app --host 0.0.0.0 --port 8000 --reload"
+      }
+    },
+    "build": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "uv run python -m compileall ml"
+      }
+    },
+    "etl": {
+      "executor": "nx:run-commands",
+      "cache": true,
+      "inputs": [
+        "default",
+        "{workspaceRoot}/ml/configs/data/**/*.yaml"
+      ],
+      "outputs": ["{workspaceRoot}/ml/data/processed"],
+      "options": {
+        "command": "uv run python -m ml.data.etl --config ml/configs/data/default.yaml --output ml/data/processed"
+      }
+    },
+    "train": {
+      "executor": "nx:run-commands",
+      "cache": true,
+      "dependsOn": ["etl"],
+      "inputs": [
+        "default",
+        "{workspaceRoot}/ml/configs/train/**/*.yaml",
+        "{workspaceRoot}/ml/configs/data/**/*.yaml",
+        "{workspaceRoot}/ml/data/processed/**"
+      ],
+      "outputs": [
+        "{workspaceRoot}/ml/models/weights",
+        "{workspaceRoot}/ml/tensorboard"
+      ],
+      "options": {
+        "command": "uv run python -m ml.models.train --config ml/configs/train/default.yaml --dataset ml/data/processed/dataset.pt --weights ml/models/weights/model.pt"
+      }
+    },
+    "lint": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "uv run ruff check ml"
+      }
+    },
+    "typecheck": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "uv run mypy ml"
+      }
+    },
+    "test": {
+      "executor": "nx:run-commands",
+      "options": {
+        "command": "uv run pytest ml -v"
+      }
+    }
+  }
+}

nx.json

@@ -0,0 +1,50 @@
+{
+  "$schema": "./node_modules/nx/schemas/nx-schema.json",
+  "namedInputs": {
+    "default": ["{projectRoot}/**/*", "sharedGlobals"],
+    "production": [
+      "default",
+      "!{projectRoot}/**/*.spec.*",
+      "!{projectRoot}/**/*.test.*",
+      "!{projectRoot}/**/__tests__/**"
+    ],
+    "sharedGlobals": [
+      "{workspaceRoot}/pyproject.toml",
+      "{workspaceRoot}/uv.lock",
+      "{workspaceRoot}/Makefile",
+      "{workspaceRoot}/.env.example"
+    ]
+  },
+  "targetDefaults": {
+    "build": {
+      "cache": true,
+      "inputs": ["production", "^production"],
+      "dependsOn": ["^build"]
+    },
+    "lint": {
+      "cache": true,
+      "inputs": ["default", "^default"]
+    },
+    "typecheck": {
+      "cache": true,
+      "inputs": ["default", "^default"]
+    },
+    "test": {
+      "cache": true,
+      "inputs": ["default", "^default"]
+    },
+    "etl": {
+      "cache": true,
+      "inputs": ["default", "^default"]
+    },
+    "train": {
+      "cache": true,
+      "inputs": ["default", "^default"]
+    }
+  },
+  "defaultBase": "main",
+  "workspaceLayout": {
+    "appsDir": "apps",
+    "libsDir": "."
+  }
+}

package.json

@@ -0,0 +1,19 @@
+{
+  "name": "ultiplate",
+  "version": "0.1.0",
+  "private": true,
+  "packageManager": "bun@1.2.0",
+  "scripts": {
+    "nx": "nx",
+    "graph": "nx graph",
+    "dev": "nx run webapp:dev",
+    "dev:stack": "nx run-many -t dev --projects=webapp,backend-fastapi,worker,ml --parallel=4",
+    "build": "nx run-many -t build --all",
+    "lint": "nx run-many -t lint --all",
+    "typecheck": "nx run-many -t typecheck --all",
+    "test": "nx run-many -t test --all"
+  },
+  "devDependencies": {
+    "nx": "^20.8.2"
+  }
+}

pyproject.toml

@@ -0,0 +1,51 @@
+[build-system]
+requires = ["setuptools>=69", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "ultiplate"
+version = "0.1.0"
+description = "AI-native full-stack template with web, backend, worker, and ML apps"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+  "anthropic",
+  "beautifulsoup4",
+  "celery[redis]",
+  "fastapi",
+  "flask",
+  "flask-cors",
+  "pydantic",
+  "python-dotenv",
+  "python-logging-loki",
+  "pyyaml",
+  "redis",
+  "requests",
+  "seleniumbase",
+  "streamlit",
+  "tensorboard",
+  "torch",
+  "tqdm",
+  "uvicorn[standard]",
+]
+
+[project.optional-dependencies]
+mlflow = ["mlflow"]
+
+[dependency-groups]
+dev = [
+  "black",
+  "mypy",
+  "pytest",
+  "ruff",
+]
+
+[tool.setuptools]
+include-package-data = true
+
+[tool.setuptools.packages.find]
+include = ["alveslib*"]
+exclude = ["apps*", "ml*", "tests*"]
+
+[tool.uv]
+default-groups = ["dev"]

requirements.txt

@@ -0,0 +1,33 @@
+# Legacy fallback only. Primary deps live in pyproject.toml.
+# Core - always installed
+python-dotenv
+requests
+tqdm
+
+# Logging (alveslib)
+python-logging-loki
+
+# Backend (fastapi or flask)
+fastapi
+flask
+flask-cors
+uvicorn[standard]
+pydantic
+
+# Worker (Celery + Redis)
+celery[redis]
+redis
+
+# Scraper (alveslib)
+seleniumbase
+beautifulsoup4
+
+# Minimal webapp
+streamlit
+
+# AI / Agent SDK
+anthropic
+
+# ML (heavy - comment out if not needed)
+torch
+tensorboard

src/main.py

@@ -0,0 +1,22 @@
+from alveslib import get_logger
+
+
+def main():
+    logger = get_logger("example_service", level="DEBUG")
+
+    logger.info("Service starting up")
+    logger.debug("This is debug information")
+    logger.warning("This is a warning")
+
+    try:
+        # Simulate some work
+        result = 10 / 2
+        logger.info(f"Calculation result: {result}")
+    except Exception as e:
+        logger.error(f"Error occurred: {e}", exc_info=True)
+
+    logger.info("Service shutting down")
+
+
+if __name__ == "__main__":
+    main()