Changement d'architecture demande par l'utilisateur : le dataset d'entrainement (TECH_STEP_TRAINING_DATA) quitte apps/api pour vivre entierement dans services/tech-step-intent-service (intent_service/training_data.py). Ce service est desormais autonome : il s'entraine lui-meme une seule fois, a son propre demarrage (PipelineRegistry.initialize, dans le lifespan FastAPI), sans plus dependre d'un POST /v1/train pousse par apps/api (route supprimee). apps/api ne connait plus aucune technique/synonyme, uniquement le resultat de POST /v1/process. Corpus enrichi avec les 48 techniques du lexique fourni (Arroser, Appertiser, Braiser, Caraméliser, Confire, Julienne/Brunoise/Mirepoix/ Paysanne, Cuire à blanc/au bain-marie/à l'étouffée, Déglacer variantes, Emulsionner, Glacer, Pocher, Réduire, Suer, Zester, etc.), soit 74 techniques au total (26 + 48). Integration complete bout en bout : - reference-seed-data.ts : 48 nouvelles entrees TECH_STEPS - apps/web/locales/fr/translation.json : libelles francais correspondants - "Mitonner" fondu comme synonyme de simmer (pas une technique distincte, sa propre definition le dit) - "Blanchir un oeuf" (whiskPale) distingue de "Blanchir un legume" (blanch, existant) via des synonymes en phrase complete plutot qu'au mot nu — filter_spans (deja en place) resout la collision par specificite Impact performance mesure : le corpus elargi (74 classes vs 26) rend l'entrainement bien plus lent a nombre d'iterations egal (150 iterations depassait 17 minutes par run de test) — reduit a 40 iterations apres mesures repetees en local (~200s/locale, ~400s pour fr+en combines). docker-compose.yml (healthcheck start_period 600s), CI (timeout curl 600s) et le README du service documentent ce nouveau temps de demarrage. CONFIDENCE_THRESHOLD recalibre a 0.2 par verification manuelle (0.75 puis 0.45 ne tenaient plus compte tenu du nombre de classes) — marque explicitement comme placeholder en attendant une vraie repasse de calibrate-tech-step-threshold.ts (necessite Postgres, indisponible dans cet environnement). Verifie : 28/28 tests pytest du service (suite complete re-ecrite pour s'entrainer une seule fois par session sur le vrai corpus, fixture partagee dans conftest.py), lint + build complets du monorepo. La suite Mocha d'apps/api reste a confirmer via CI (le root hook mocha n'attend plus l'entrainement, seulement CI's propre attente sur /health). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
130 lines
5.9 KiB
YAML
130 lines
5.9 KiB
YAML
services:
|
|
postgres:
|
|
image: postgres:16-alpine
|
|
restart: unless-stopped
|
|
environment:
|
|
# No defaults on purpose: POSTGRES_USER/PASSWORD/DB must be set in your
|
|
# local, git-ignored .env (see .env.example). Compose fails loudly if
|
|
# they're missing instead of falling back to a guessable credential.
|
|
POSTGRES_USER: ${POSTGRES_USER:?set POSTGRES_USER in .env}
|
|
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?set POSTGRES_PASSWORD in .env}
|
|
POSTGRES_DB: ${POSTGRES_DB:?set POSTGRES_DB in .env}
|
|
ports:
|
|
- "${POSTGRES_PORT:-5432}:5432"
|
|
volumes:
|
|
- postgres_data:/var/lib/postgresql/data
|
|
healthcheck:
|
|
test: ["CMD-SHELL", "pg_isready -U $$POSTGRES_USER"]
|
|
interval: 5s
|
|
timeout: 5s
|
|
retries: 5
|
|
|
|
# Single service serving both the API and the built frontend (see
|
|
# apps/api/Dockerfile) — no separate nginx/web container, no cross-origin
|
|
# CORS_ORIGIN to keep in sync between two ports.
|
|
app:
|
|
build:
|
|
context: .
|
|
dockerfile: apps/api/Dockerfile
|
|
restart: unless-stopped
|
|
environment:
|
|
NODE_ENV: production
|
|
PORT: 3000
|
|
# Uses the "postgres" service name, not localhost/POSTGRES_PORT —
|
|
# container-to-container traffic stays on the compose network and
|
|
# always targets Postgres's internal port (5432).
|
|
DATABASE_URL: "postgresql://${POSTGRES_USER:?set POSTGRES_USER in .env}:${POSTGRES_PASSWORD:?set POSTGRES_PASSWORD in .env}@postgres:5432/${POSTGRES_DB:?set POSTGRES_DB in .env}?schema=public"
|
|
JWT_SECRET: ${JWT_SECRET:?set JWT_SECRET in .env}
|
|
# Unset by default (falls back to NODE_ENV === "production", i.e.
|
|
# Secure cookie required) — set COOKIE_SECURE=false in .env only if
|
|
# this deployment is reachable over plain HTTP (no TLS in front of
|
|
# it yet), otherwise the session cookie never comes back and every
|
|
# authenticated request 401s despite login succeeding. See its doc
|
|
# comment in apps/api/src/config/env.ts.
|
|
COOKIE_SECURE: ${COOKIE_SECURE:-}
|
|
# Shared with the `tech-step-llm-worker` service below — see
|
|
# requireInternalWorker's doc comment
|
|
# (apps/api/src/middlewares/require-internal-worker.ts). Unset by
|
|
# default: `/internal/tech-steps/*` fails closed rather than open
|
|
# for a deployment that doesn't run the worker at all.
|
|
INTERNAL_WORKER_SECRET: ${INTERNAL_WORKER_SECRET:-}
|
|
# Compose network service name, not localhost — same reasoning as
|
|
# DATABASE_URL above. Unlike INTERNAL_WORKER_SECRET, no `:-` fallback:
|
|
# tech-step-intent-service is a core dependency (see its own entry
|
|
# below), not an optional background job.
|
|
INTENT_SERVICE_BASE_URL: "http://tech-step-intent-service:8000"
|
|
INTENT_SERVICE_SECRET: ${INTENT_SERVICE_SECRET:?set INTENT_SERVICE_SECRET in .env}
|
|
ports:
|
|
- "${APP_PORT:-3000}:3000"
|
|
depends_on:
|
|
postgres:
|
|
condition: service_healthy
|
|
tech-step-intent-service:
|
|
condition: service_healthy
|
|
|
|
# spaCy-based NER + intent classification microservice
|
|
# (services/tech-step-intent-service) — `app` delegates all tech-step
|
|
# detection to it over HTTP (see `IntentServiceClient`,
|
|
# apps/api/src/lib/recipe-matching/intent-service-client.ts). Unlike
|
|
# `tech-step-llm-worker` below, **not optional**: without it, `app` can no
|
|
# longer detect any cooking technique in a recipe step at all. No exposed
|
|
# port — reachable only from `app` on the compose network, nothing ever
|
|
# calls into it from outside.
|
|
tech-step-intent-service:
|
|
build:
|
|
context: .
|
|
dockerfile: services/tech-step-intent-service/Dockerfile
|
|
restart: unless-stopped
|
|
environment:
|
|
INTENT_SERVICE_SECRET: ${INTENT_SERVICE_SECRET:?set INTENT_SERVICE_SECRET in .env}
|
|
healthcheck:
|
|
# No curl/wget in the python:3.12-slim base image — a one-line Python
|
|
# request is the healthcheck for a service that's already guaranteed
|
|
# to have Python (see this service's Dockerfile).
|
|
test:
|
|
[
|
|
"CMD",
|
|
"python",
|
|
"-c",
|
|
"import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=2)",
|
|
]
|
|
interval: 15s
|
|
timeout: 3s
|
|
retries: 5
|
|
# This service trains itself from scratch on every start (no model
|
|
# ever persisted to disk, see its own README) — `/health` only
|
|
# returns 200 once that's done, not just once the base spaCy models
|
|
# are loaded. Measured at ~200s per locale (~400s for fr+en combined)
|
|
# against the current ~74-technique corpus
|
|
# (`intent_service/training_data.py`) — `start_period` generous
|
|
# enough that failing checks during that whole window never count
|
|
# against `retries` (which would otherwise flip this container to
|
|
# "unhealthy" mid-training, blocking `app`'s own
|
|
# `depends_on: condition: service_healthy` indefinitely).
|
|
start_period: 600s
|
|
|
|
# Deliberately its own image, not built into `app`'s (see
|
|
# services/tech-step-llm-worker/Dockerfile's own doc comment) — a
|
|
# long-lived process with no exposed port (nothing ever calls *into* it,
|
|
# it only ever calls out to `app`). Optional: an `INTERNAL_WORKER_SECRET`-
|
|
# less deployment can omit this service entirely and `app` still runs
|
|
# fine, just without the offline audit/feedback-loop jobs.
|
|
tech-step-llm-worker:
|
|
build:
|
|
context: .
|
|
dockerfile: services/tech-step-llm-worker/Dockerfile
|
|
restart: unless-stopped
|
|
depends_on:
|
|
- app
|
|
environment:
|
|
API_BASE_URL: "http://app:3000"
|
|
INTERNAL_WORKER_SECRET: ${INTERNAL_WORKER_SECRET:?set INTERNAL_WORKER_SECRET in .env to run this service}
|
|
TECH_STEP_WORKER_CRON: ${TECH_STEP_WORKER_CRON:-0 3 * * 0}
|
|
volumes:
|
|
# GGUF weights persist across restarts — see this service's own
|
|
# Dockerfile doc comment on its VOLUME declaration.
|
|
- tech_step_llm_worker_models:/worker/models
|
|
|
|
volumes:
|
|
postgres_data:
|
|
tech_step_llm_worker_models:
|