archiet-microcodegen-flask 0.1.0

PRD text → working Flask + SQLAlchemy app ZIP. Pure stdlib, zero dependencies, zero LLM calls.

archiet-microcodegen-flask

PRD text → working Flask + SQLAlchemy app → ZIP, in <1400 LOC, pure stdlib, zero LLM calls. Inspired by Karpathy's micrograd: this file is the complete algorithm.

Built on Archiet — AI-native architecture-to-code platform.

Install

pip install archiet-microcodegen-flask

Use

# Write ZIP to disk
archiet-microcodegen-flask path/to/prd.md --out ./out/

# Pipe ZIP to stdout
archiet-microcodegen-flask path/to/prd.md > app.zip

As a library:

from archiet_microcodegen_flask import microcodegen_flask

prd_text = open("prd.md").read()
zip_bytes = microcodegen_flask(prd_text)

What you get

The generated output is a working Flask + PostgreSQL app:

app/__init__.py          Flask app factory — create_app()
app/extensions.py        db, jwt, migrate singletons
app/auth/routes.py       register / login / logout / me
app/models/user.py       User model
app/models/<entity>.py   One SQLAlchemy model per entity
app/routes/<entity>.py   One Blueprint per entity (full CRUD)
config.py                JWT_TOKEN_LOCATION=["cookies"], JWT_COOKIE_HTTPONLY=True
manage.py                Flask CLI entrypoint
requirements.txt         flask, flask-sqlalchemy, flask-jwt-extended, flask-migrate, psycopg2-binary
docker-compose.yml       Postgres 16 with healthcheck-gated startup
Dockerfile               python:3.12-slim, port 5000
.env.example             DATABASE_URL, JWT_SECRET_KEY, SECRET_KEY
tests/test_app.py        pytest smoke tests (register, login, health)
ARCHITECTURE.md          ArchiMate 3.2 element map
openapi.yaml             OpenAPI 3.1 spec
GENOME.json              Intermediate representation (for debugging/regeneration)
README.md                Quick-start for the generated app

The four stages

1. parse_prd(text) → manifest — regex extraction of entities, fields, user stories, integrations
2. manifest_to_genome(manifest) → genome — maps to canonical IR with ArchiMate 3.2 element typing
3. render_genome(genome) → {path: content} — string.Template-based Flask rendering
4. pack(files) → bytes — stdlib zipfile

Auth — httpOnly cookies, non-negotiable

• JWT_TOKEN_LOCATION = ["cookies"]
• JWT_COOKIE_HTTPONLY = True
• JWT_COOKIE_SAMESITE = "Lax"
• Register → sets cookie. Login → sets cookie. Logout → clears cookie.
• NEVER localStorage. NEVER Authorization header in response body.

Why this exists

Spec-driven architecture before vibecoding. The genome is an ArchiMate 3.2 intermediate representation — your PRD becomes an architecture document, not just a prompt.

The full Archiet platform adds:

• LLM-powered PRD extraction (chunked, overlap+dedup, handles natural language)
• 12+ stack renderers (FastAPI, Flask, Django, NestJS, Laravel, Go, Java, Rails, .NET, Tauri+Rust, Salesforce, SAP CAP)
• Capability emission, frontend (Next.js / Expo), stub-filling, quality scoring, delivery gates
• Cross-stack parity enforcement and verification

But none of that changes the core algorithm. If a bug doesn't reproduce here, it's in an efficiency layer.

What's NOT included

• No LLM calls (deterministic zone by design)
• No frontend, no mobile, no payment integration, no rate limiting, no audit logging
• No multi-stack output (Flask only; see archiet-microcodegen for the FastAPI variant)

License

MIT. See LICENSE.

Links

• Source: github.com/aniekanasuquookono-web/archiet
• FastAPI variant: archiet-microcodegen
• Full platform: archiet.com