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159 changed files with 1465 additions and 18163 deletions

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@ -1,44 +0,0 @@
# git-cliff changelog configuration for Kiwi
# See: https://git-cliff.org/docs/configuration
[changelog]
header = """
# Changelog\n
"""
body = """
{% if version %}\
## [{{ version | trim_start_matches(pat="v") }}] - {{ timestamp | date(format="%Y-%m-%d") }}
{% else %}\
## [Unreleased]
{% endif %}\
{% for group, commits in commits | group_by(attribute="group") %}
### {{ group | upper_first }}
{% for commit in commits %}
- {% if commit.scope %}**{{ commit.scope }}:** {% endif %}{{ commit.message | upper_first }}\
{% endfor %}
{% endfor %}\n
"""
trim = true
[git]
conventional_commits = true
filter_unconventional = true
split_commits = false
commit_preprocessors = []
commit_parsers = [
{ message = "^feat", group = "Features" },
{ message = "^fix", group = "Bug Fixes" },
{ message = "^perf", group = "Performance" },
{ message = "^refactor", group = "Refactoring" },
{ message = "^docs", group = "Documentation" },
{ message = "^test", group = "Testing" },
{ message = "^chore", group = "Chores" },
{ message = "^ci", group = "CI/CD" },
{ message = "^revert", group = "Reverts" },
]
filter_commits = false
tag_pattern = "v[0-9].*"
skip_tags = ""
ignore_tags = ""
topo_order = false
sort_commits = "oldest"

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@ -51,12 +51,6 @@ ENABLE_OCR=false
DEBUG=false
CLOUD_MODE=false
DEMO_MODE=false
# Product identifier reported in cf-orch coordinator analytics for per-app breakdown
CF_APP_NAME=kiwi
# USE_ORCH_SCHEDULER: use coordinator-aware multi-GPU scheduler instead of local FIFO.
# Unset = auto-detect: true if CLOUD_MODE or circuitforge_orch is installed (paid+ local).
# Set false to force LocalScheduler even when cf-orch is present.
# USE_ORCH_SCHEDULER=false
# Cloud mode (set in compose.cloud.yml; also set here for reference)
# CLOUD_DATA_ROOT=/devl/kiwi-cloud-data
@ -74,14 +68,9 @@ CF_APP_NAME=kiwi
# HEIMDALL_URL=https://license.circuitforge.tech
# HEIMDALL_ADMIN_TOKEN=
# Directus JWT (must match cf-directus SECRET env var exactly, including base64 == padding)
# Directus JWT (must match cf-directus SECRET env var)
# DIRECTUS_JWT_SECRET=
# E2E test account (Directus — free tier, used by automated tests)
# E2E_TEST_EMAIL=e2e@circuitforge.tech
# E2E_TEST_PASSWORD=
# E2E_TEST_USER_ID=
# In-app feedback → Forgejo issue creation
# FORGEJO_API_TOKEN=
# FORGEJO_REPO=Circuit-Forge/kiwi
@ -94,10 +83,3 @@ CF_APP_NAME=kiwi
# INSTACART_AFFILIATE_ID=circuitforge
# Walmart Impact network affiliate ID (inline, path-based redirect)
# WALMART_AFFILIATE_ID=
# Community PostgreSQL — shared across CF products (cloud only; leave unset for local dev)
# Points at cf-orch's cf-community-postgres container (port 5434 on the orch host).
# When unset, community write paths fail soft with a plain-language message.
# COMMUNITY_DB_URL=postgresql://cf_community:changeme@cf-orch-host:5434/cf_community
# COMMUNITY_PSEUDONYM_SALT=change-this-to-a-random-32-char-string

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@ -1,62 +0,0 @@
# Kiwi CI — lint, type-check, test on PR/push
# Full-stack: FastAPI (Python) + Vue 3 SPA (Node)
# Adapted from Circuit-Forge/cf-agents workflows/ci.yml (cf-agents#4 tracks the
# upstream ci-fullstack.yml variant; update this file when that lands).
#
# Note: frontend has no test suite yet — CI runs typecheck only.
# Add `npm run test` when vitest is wired (kiwi#XX).
#
# circuitforge-core is not on PyPI — installed from Forgejo git (public repo).
name: CI
on:
push:
branches: [main, 'feature/**', 'fix/**']
pull_request:
branches: [main]
jobs:
backend:
name: Backend (Python)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
cache: pip
- name: Install circuitforge-core
run: pip install git+https://git.opensourcesolarpunk.com/Circuit-Forge/circuitforge-core.git@main
- name: Install dependencies
run: pip install -e ".[dev]" || pip install -e . pytest pytest-asyncio httpx ruff
- name: Lint
run: ruff check .
- name: Test
run: pytest tests/ -v --tb=short
frontend:
name: Frontend (Vue)
runs-on: ubuntu-latest
defaults:
run:
working-directory: frontend
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '20'
cache: npm
cache-dependency-path: frontend/package-lock.json
- name: Install dependencies
run: npm ci
- name: Type check
run: npx vue-tsc --noEmit

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@ -1,34 +0,0 @@
# Mirror push to GitHub and Codeberg on every push to main or tag.
# Copied from Circuit-Forge/cf-agents workflows/mirror.yml
# Required secrets: GITHUB_MIRROR_TOKEN, CODEBERG_MIRROR_TOKEN
name: Mirror
on:
push:
branches: [main]
tags: ['v*']
jobs:
mirror:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Mirror to GitHub
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_MIRROR_TOKEN }}
REPO: ${{ github.event.repository.name }}
run: |
git remote add github "https://x-access-token:${GITHUB_TOKEN}@github.com/CircuitForgeLLC/${REPO}.git"
git push github --mirror
- name: Mirror to Codeberg
env:
CODEBERG_TOKEN: ${{ secrets.CODEBERG_MIRROR_TOKEN }}
REPO: ${{ github.event.repository.name }}
run: |
git remote add codeberg "https://CircuitForge:${CODEBERG_TOKEN}@codeberg.org/CircuitForge/${REPO}.git"
git push codeberg --mirror

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@ -1,71 +0,0 @@
# Tag-triggered release workflow.
# Generates changelog and creates Forgejo release on v* tags.
# Copied from Circuit-Forge/cf-agents workflows/release.yml
#
# Docker push is intentionally disabled — BSL 1.1 registry policy not yet resolved.
# Tracked in Circuit-Forge/cf-agents#3. Re-enable the Docker steps when that lands.
#
# Required secrets: FORGEJO_RELEASE_TOKEN
# (GHCR_TOKEN not needed until Docker push is enabled)
name: Release
on:
push:
tags: ['v*']
jobs:
release:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
# ── Changelog ────────────────────────────────────────────────────────────
- name: Generate changelog
uses: orhun/git-cliff-action@v3
id: cliff
with:
config: .cliff.toml
args: --latest --strip header
env:
OUTPUT: CHANGES.md
# ── Docker (disabled — BSL registry policy pending cf-agents#3) ──────────
# - name: Set up QEMU
# uses: docker/setup-qemu-action@v3
# - name: Set up Buildx
# uses: docker/setup-buildx-action@v3
# - name: Log in to GHCR
# uses: docker/login-action@v3
# with:
# registry: ghcr.io
# username: ${{ github.actor }}
# password: ${{ secrets.GHCR_TOKEN }}
# - name: Build and push Docker image
# uses: docker/build-push-action@v6
# with:
# context: .
# push: true
# platforms: linux/amd64,linux/arm64
# tags: |
# ghcr.io/circuitforgellc/kiwi:${{ github.ref_name }}
# ghcr.io/circuitforgellc/kiwi:latest
# cache-from: type=gha
# cache-to: type=gha,mode=max
# ── Forgejo Release ───────────────────────────────────────────────────────
- name: Create Forgejo release
env:
FORGEJO_TOKEN: ${{ secrets.FORGEJO_RELEASE_TOKEN }}
REPO: ${{ github.event.repository.name }}
TAG: ${{ github.ref_name }}
NOTES: ${{ steps.cliff.outputs.content }}
run: |
curl -sS -X POST \
"https://git.opensourcesolarpunk.com/api/v1/repos/Circuit-Forge/${REPO}/releases" \
-H "Authorization: token ${FORGEJO_TOKEN}" \
-H "Content-Type: application/json" \
-d "$(jq -n --arg tag "$TAG" --arg body "$NOTES" \
'{tag_name: $tag, name: $tag, body: $body}')"

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@ -1,59 +0,0 @@
# Kiwi CI — runs on GitHub mirror for public credibility badge.
# Forgejo (.forgejo/workflows/ci.yml) is the canonical CI — keep these in sync.
# No Forgejo-specific secrets used here; circuitforge-core is public on Forgejo.
#
# Note: frontend has no test suite yet — CI runs typecheck only.
# Add 'npm run test' when vitest is wired.
name: CI
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
backend:
name: Backend (Python)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
cache: pip
- name: Install circuitforge-core
run: pip install git+https://git.opensourcesolarpunk.com/Circuit-Forge/circuitforge-core.git@main
- name: Install dependencies
run: pip install -e . pytest pytest-asyncio httpx ruff
- name: Lint
run: ruff check .
- name: Test
run: pytest tests/ -v --tb=short
frontend:
name: Frontend (Vue)
runs-on: ubuntu-latest
defaults:
run:
working-directory: frontend
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '20'
cache: npm
cache-dependency-path: frontend/package-lock.json
- name: Install dependencies
run: npm ci
- name: Type check
run: npx vue-tsc --noEmit

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@ -1,34 +0,0 @@
# Kiwi gitleaks config — extends base CircuitForge config with local rules
[extend]
path = "/Library/Development/CircuitForge/circuitforge-hooks/gitleaks.toml"
# ── Global allowlist ──────────────────────────────────────────────────────────
# Amazon grocery department IDs (rh=n:<10-digit>) false-positive as phone
# numbers. locale_config.py is a static lookup table with no secrets.
[allowlist]
# Amazon grocery dept IDs (rh=n:<digits>) false-positive as phone numbers.
regexes = [
'''rh=n:\d{8,12}''',
]
# ── Test fixture allowlists ───────────────────────────────────────────────────
[[rules]]
id = "cf-generic-env-token"
description = "Generic KEY=<token> in env-style assignment — catches FORGEJO_API_TOKEN=hex etc."
regex = '''(?i)(token|secret|key|password|passwd|pwd|api_key)\s*[=:]\s*['"]?[A-Za-z0-9\-_]{20,}['"]?'''
[rules.allowlist]
paths = [
'.*test.*',
]
regexes = [
'api_key:\s*ollama',
'api_key:\s*any',
'your-[a-z\-]+-here',
'replace-with-',
'xxxx',
'test-fixture-',
'CFG-KIWI-TEST-',
]

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@ -11,23 +11,13 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
COPY circuitforge-core/ ./circuitforge-core/
RUN conda run -n base pip install --no-cache-dir -e ./circuitforge-core
# Install circuitforge-orch — needed for the cf-orch-agent sidecar (compose.override.yml)
COPY circuitforge-orch/ ./circuitforge-orch/
# Create kiwi conda env and install app
COPY kiwi/environment.yml .
RUN conda env create -f environment.yml
COPY kiwi/ ./kiwi/
# Remove gitignored config files that may exist locally — defense-in-depth.
# The parent .dockerignore should exclude these, but an explicit rm guarantees
# they never end up in the cloud image regardless of .dockerignore placement.
RUN rm -f /app/kiwi/.env
# Install cf-core and cf-orch into the kiwi env BEFORE installing kiwi
# Install cf-core into the kiwi env BEFORE installing kiwi (kiwi lists it as a dep)
RUN conda run -n kiwi pip install --no-cache-dir -e /app/circuitforge-core
RUN conda run -n kiwi pip install --no-cache-dir -e /app/circuitforge-orch
WORKDIR /app/kiwi
RUN conda run -n kiwi pip install --no-cache-dir -e .

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@ -10,8 +10,6 @@ Scan barcodes, photograph receipts, and get recipe ideas based on what you alrea
**Status:** Beta · CircuitForge LLC
**[Documentation](https://docs.circuitforge.tech/kiwi/)** · [circuitforge.tech](https://circuitforge.tech)
---
## What it does
@ -23,7 +21,7 @@ Scan barcodes, photograph receipts, and get recipe ideas based on what you alrea
- **Receipt OCR** — extract line items from receipt photos automatically (Paid tier, BYOK-unlockable)
- **Recipe suggestions** — four levels from pantry-match to full LLM generation (Paid tier, BYOK-unlockable)
- **Style auto-classifier** — LLM suggests style tags (comforting, hands-off, quick, etc.) for saved recipes (Paid tier, BYOK-unlockable)
- **Leftover mode** — prioritize nearly-expired items in recipe ranking (Free, 5/day; unlimited at Paid+)
- **Leftover mode** — prioritize nearly-expired items in recipe ranking (Premium tier)
- **LLM backend config** — configure inference via `circuitforge-core` env-var system; BYOK unlocks Paid AI features at any tier
- **Feedback FAB** — in-app feedback button; status probed on load, hidden if CF feedback endpoint unreachable
@ -70,7 +68,7 @@ cp .env.example .env
| LLM style auto-classifier | — | BYOK | ✓ |
| Meal planning | — | ✓ | ✓ |
| Multi-household | — | — | ✓ |
| Leftover mode (5/day) | ✓ | ✓ | ✓ |
| Leftover mode | — | — | ✓ |
BYOK = bring your own LLM backend (configure `~/.config/circuitforge/llm.yaml`)

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@ -6,7 +6,6 @@ from __future__ import annotations
import asyncio
import logging
import re
import sqlite3
from datetime import datetime, timezone
from fastapi import APIRouter, Depends, HTTPException, Request, Response
@ -20,37 +19,37 @@ logger = logging.getLogger(__name__)
router = APIRouter(prefix="/community", tags=["community"])
# Module-level KiwiCommunityStore — None when COMMUNITY_DB_URL is not set.
# Browse endpoints degrade gracefully to empty; write endpoints return 503.
_community_store = None
def _get_community_store():
"""Return the module-level KiwiCommunityStore, or None if community DB is unavailable."""
return _community_store
def init_community_store(community_db_url: str | None) -> None:
"""Called from main.py lifespan when COMMUNITY_DB_URL is set."""
global _community_store
if not community_db_url:
logger.info(
"COMMUNITY_DB_URL not set — community write features disabled. "
"Browse still works via cloud feed."
"Browse still works via cloud fallback."
)
return
from circuitforge_core.community import CommunityDB
from app.services.community.community_store import KiwiCommunityStore
db = CommunityDB(dsn=community_db_url)
db.run_migrations()
_community_store = KiwiCommunityStore(db)
logger.info("Community store initialized.")
try:
from circuitforge_core.community import CommunityDB
from app.services.community.community_store import KiwiCommunityStore
db = CommunityDB(dsn=community_db_url)
db.run_migrations()
_community_store = KiwiCommunityStore(db)
logger.info("Community store initialized (PostgreSQL).")
except Exception as exc:
logger.warning("Community store init failed — community writes disabled: %s", exc)
def _visible(post, session=None) -> bool:
"""Return False for premium-tier posts when the session is not paid/premium."""
tier = getattr(post, "tier", None)
if tier == "premium":
if session is None or getattr(session, "tier", None) not in ("paid", "premium"):
return False
return True
# ── Browse (no auth required — Free tier) ────────────────────────────────────
@router.get("/posts")
async def list_posts(
@ -60,15 +59,10 @@ async def list_posts(
page: int = 1,
page_size: int = 20,
):
"""Paginated community post list. Available on all tiers (read-only)."""
store = _get_community_store()
if store is None:
return {
"posts": [],
"total": 0,
"page": page,
"page_size": page_size,
"note": "Community DB not available on this instance.",
}
return {"posts": [], "total": 0, "note": "Community DB not available on this instance."}
dietary = [t.strip() for t in dietary_tags.split(",")] if dietary_tags else None
allergen_ex = [t.strip() for t in allergen_exclude.split(",")] if allergen_exclude else None
@ -82,12 +76,12 @@ async def list_posts(
dietary_tags=dietary,
allergen_exclude=allergen_ex,
)
visible = [_post_to_dict(p) for p in posts if _visible(p)]
return {"posts": visible, "total": len(visible), "page": page, "page_size": page_size}
return {"posts": [_post_to_dict(p) for p in posts], "page": page, "page_size": page_size}
@router.get("/posts/{slug}")
async def get_post(slug: str, request: Request):
"""Single post. Returns AP JSON-LD when Accept: application/activity+json."""
store = _get_community_store()
if store is None:
raise HTTPException(status_code=503, detail="Community DB not available on this instance.")
@ -97,7 +91,7 @@ async def get_post(slug: str, request: Request):
raise HTTPException(status_code=404, detail="Post not found.")
accept = request.headers.get("accept", "")
if "application/activity+json" in accept or "application/ld+json" in accept:
if "application/activity+json" in accept:
from app.services.community.ap_compat import post_to_ap_json_ld
base_url = str(request.base_url).rstrip("/")
return post_to_ap_json_ld(_post_to_dict(post), base_url=base_url)
@ -107,6 +101,7 @@ async def get_post(slug: str, request: Request):
@router.get("/feed.rss")
async def get_rss_feed(request: Request):
"""RSS 2.0 feed of recent community posts."""
store = _get_community_store()
posts_data: list[dict] = []
if store is not None:
@ -120,6 +115,7 @@ async def get_rss_feed(request: Request):
@router.get("/local-feed")
async def local_feed():
"""LAN peer endpoint: last 50 posts from this instance. No auth required."""
store = _get_community_store()
if store is None:
return []
@ -127,54 +123,18 @@ async def local_feed():
return [_post_to_dict(p) for p in posts]
@router.get("/hall-of-chaos")
async def hall_of_chaos():
"""Hidden easter egg endpoint -- returns the 10 most chaotic bloopers."""
store = _get_community_store()
if store is None:
return {"posts": [], "chaos_level": 0}
posts = await asyncio.to_thread(
store.list_posts, limit=10, post_type="recipe_blooper"
)
return {
"posts": [_post_to_dict(p) for p in posts],
"chaos_level": len(posts),
}
_VALID_POST_TYPES = {"plan", "recipe_success", "recipe_blooper"}
_MAX_TITLE_LEN = 200
_MAX_TEXT_LEN = 2000
def _validate_publish_body(body: dict) -> None:
"""Raise HTTPException(422) for any invalid fields in a publish request."""
post_type = body.get("post_type", "plan")
if post_type not in _VALID_POST_TYPES:
raise HTTPException(
status_code=422,
detail=f"post_type must be one of: {', '.join(sorted(_VALID_POST_TYPES))}",
)
title = body.get("title") or ""
if len(title) > _MAX_TITLE_LEN:
raise HTTPException(status_code=422, detail=f"title exceeds {_MAX_TITLE_LEN} character limit.")
for field in ("description", "outcome_notes", "recipe_name"):
value = body.get(field)
if value and len(str(value)) > _MAX_TEXT_LEN:
raise HTTPException(status_code=422, detail=f"{field} exceeds {_MAX_TEXT_LEN} character limit.")
photo_url = body.get("photo_url")
if photo_url and not str(photo_url).startswith("https://"):
raise HTTPException(status_code=422, detail="photo_url must be an https:// URL.")
# ── Write endpoints (auth required) ──────────────────────────────────────────
@router.post("/posts", status_code=201)
async def publish_post(body: dict, session: CloudUser = Depends(get_session)):
async def publish_post(
body: dict,
session: CloudUser = Depends(get_session),
):
"""Publish a plan or outcome to the community feed. Requires Paid tier."""
from app.tiers import can_use
if not can_use("community_publish", session.tier, session.has_byok):
raise HTTPException(status_code=402, detail="Community publishing requires Paid tier.")
_validate_publish_body(body)
store = _get_community_store()
if store is None:
raise HTTPException(
@ -183,9 +143,12 @@ async def publish_post(body: dict, session: CloudUser = Depends(get_session)):
"Publishing is only available on cloud instances.",
)
# Resolve pseudonym (first-time setup inline via publish modal)
from app.services.community.community_store import get_or_create_pseudonym
db_path = session.db
def _get_pseudonym():
s = Store(session.db)
s = Store(db_path)
try:
return get_or_create_pseudonym(
store=s,
@ -194,67 +157,67 @@ async def publish_post(body: dict, session: CloudUser = Depends(get_session)):
)
finally:
s.close()
try:
pseudonym = await asyncio.to_thread(_get_pseudonym)
except ValueError as exc:
raise HTTPException(status_code=422, detail=str(exc)) from exc
pseudonym = await asyncio.to_thread(_get_pseudonym)
# Compute element snapshot from corpus recipes in the plan
recipe_ids = [slot["recipe_id"] for slot in body.get("slots", []) if slot.get("recipe_id")]
from app.services.community.element_snapshot import compute_snapshot
def _snapshot():
s = Store(session.db)
s = Store(db_path)
try:
return compute_snapshot(recipe_ids=recipe_ids, store=s)
finally:
s.close()
snapshot = await asyncio.to_thread(_snapshot)
post_type = body.get("post_type", "plan")
# Build deterministic slug
slug_title = re.sub(r"[^a-z0-9]+", "-", (body.get("title") or "plan").lower()).strip("-")
today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
post_type = body.get("post_type", "plan")
slug = f"kiwi-{_post_type_prefix(post_type)}-{pseudonym.lower().replace(' ', '')}-{today}-{slug_title}"[:120]
from circuitforge_core.community.models import CommunityPost
post = CommunityPost(
slug=slug,
pseudonym=pseudonym,
post_type=post_type,
published=datetime.now(timezone.utc),
title=(body.get("title") or "Untitled")[:_MAX_TITLE_LEN],
description=body.get("description"),
photo_url=body.get("photo_url"),
slots=body.get("slots", []),
recipe_id=body.get("recipe_id"),
recipe_name=body.get("recipe_name"),
level=body.get("level"),
outcome_notes=body.get("outcome_notes"),
seasoning_score=snapshot.seasoning_score,
richness_score=snapshot.richness_score,
brightness_score=snapshot.brightness_score,
depth_score=snapshot.depth_score,
aroma_score=snapshot.aroma_score,
structure_score=snapshot.structure_score,
texture_profile=snapshot.texture_profile,
dietary_tags=list(snapshot.dietary_tags),
allergen_flags=list(snapshot.allergen_flags),
flavor_molecules=list(snapshot.flavor_molecules),
fat_pct=snapshot.fat_pct,
protein_pct=snapshot.protein_pct,
moisture_pct=snapshot.moisture_pct,
)
try:
inserted = await asyncio.to_thread(store.insert_post, post)
except sqlite3.IntegrityError as exc:
raise HTTPException(
status_code=409,
detail="A post with this title already exists today. Try a different title.",
) from exc
from circuitforge_core.community.models import CommunityPost
post = CommunityPost(
slug=slug,
pseudonym=pseudonym,
post_type=post_type,
published=datetime.now(timezone.utc),
title=body.get("title", "Untitled"),
description=body.get("description"),
photo_url=body.get("photo_url"),
slots=body.get("slots", []),
recipe_id=body.get("recipe_id"),
recipe_name=body.get("recipe_name"),
level=body.get("level"),
outcome_notes=body.get("outcome_notes"),
seasoning_score=snapshot.seasoning_score,
richness_score=snapshot.richness_score,
brightness_score=snapshot.brightness_score,
depth_score=snapshot.depth_score,
aroma_score=snapshot.aroma_score,
structure_score=snapshot.structure_score,
texture_profile=snapshot.texture_profile,
dietary_tags=list(snapshot.dietary_tags),
allergen_flags=list(snapshot.allergen_flags),
flavor_molecules=list(snapshot.flavor_molecules),
fat_pct=snapshot.fat_pct,
protein_pct=snapshot.protein_pct,
moisture_pct=snapshot.moisture_pct,
)
except ImportError:
raise HTTPException(status_code=503, detail="Community module not available.")
inserted = await asyncio.to_thread(store.insert_post, post)
return _post_to_dict(inserted)
@router.delete("/posts/{slug}", status_code=204)
async def delete_post(slug: str, session: CloudUser = Depends(get_session)):
"""Hard-delete a post. Only succeeds if the caller is the post author (pseudonym match)."""
store = _get_community_store()
if store is None:
raise HTTPException(status_code=503, detail="Community DB not available.")
@ -265,6 +228,7 @@ async def delete_post(slug: str, session: CloudUser = Depends(get_session)):
return s.get_current_pseudonym(session.user_id)
finally:
s.close()
pseudonym = await asyncio.to_thread(_get_pseudonym)
if not pseudonym:
raise HTTPException(status_code=400, detail="No pseudonym set. Cannot delete posts.")
@ -276,6 +240,7 @@ async def delete_post(slug: str, session: CloudUser = Depends(get_session)):
@router.post("/posts/{slug}/fork", status_code=201)
async def fork_post(slug: str, session: CloudUser = Depends(get_session)):
"""Exact-copy fork: creates a new meal plan in the caller's DB with matching slots. Free."""
store = _get_community_store()
if store is None:
raise HTTPException(status_code=503, detail="Community DB not available.")
@ -286,18 +251,14 @@ async def fork_post(slug: str, session: CloudUser = Depends(get_session)):
if post.post_type != "plan":
raise HTTPException(status_code=400, detail="Only plan posts can be forked as a meal plan.")
required_slot_keys = {"day", "meal_type", "recipe_id"}
if any(not required_slot_keys.issubset(slot) for slot in post.slots):
raise HTTPException(status_code=400, detail="Post contains malformed slots and cannot be forked.")
from datetime import date
week_start = date.today().strftime("%Y-%m-%d")
def _create_plan():
s = Store(session.db)
try:
meal_types = list({slot["meal_type"] for slot in post.slots})
plan = s.create_meal_plan(week_start=week_start, meal_types=meal_types or ["dinner"])
week_start = date.today().strftime("%Y-%m-%d")
meal_types = list({slot["meal_type"] for slot in post.slots}) or ["dinner"]
plan = s.create_meal_plan(week_start=week_start, meal_types=meal_types)
for slot in post.slots:
s.assign_recipe_to_slot(
plan_id=plan["id"],
@ -315,14 +276,34 @@ async def fork_post(slug: str, session: CloudUser = Depends(get_session)):
@router.post("/posts/{slug}/fork-adapt", status_code=201)
async def fork_adapt_post(slug: str, session: CloudUser = Depends(get_session)):
"""Fork with LLM pantry adaptation. Paid/BYOK. Returns suggestions for user review."""
from app.tiers import can_use
if not can_use("community_fork_adapt", session.tier, session.has_byok):
raise HTTPException(status_code=402, detail="Fork with adaptation requires Paid tier or BYOK.")
# Stub: full LLM adaptation deferred
raise HTTPException(status_code=501, detail="Fork-adapt not yet implemented.")
store = _get_community_store()
if store is None:
raise HTTPException(status_code=503, detail="Community DB not available.")
post = await asyncio.to_thread(store.get_post_by_slug, slug)
if post is None:
raise HTTPException(status_code=404, detail="Post not found.")
# BSL 1.1 call site — LLM adaptation
from app.services.meal_plan.llm_planner import adapt_plan_to_pantry
suggestions = await adapt_plan_to_pantry(
slots=list(post.slots),
db_path=session.db,
tier=session.tier,
has_byok=session.has_byok,
)
return {"suggestions": suggestions, "forked_from": slug}
# ── Helpers ───────────────────────────────────────────────────────────────────
def _post_to_dict(post) -> dict:
"""Convert a CommunityPost (frozen dataclass) to a JSON-serializable dict."""
return {
"slug": post.slug,
"pseudonym": post.pseudonym,

View file

@ -1,11 +1,9 @@
"""Export endpoints — CSV and JSON export of user data."""
"""Export endpoints — CSV/Excel of receipt and inventory data."""
from __future__ import annotations
import asyncio
import csv
import io
import json
from datetime import datetime, timezone
from fastapi import APIRouter, Depends
from fastapi.responses import StreamingResponse
@ -47,33 +45,3 @@ async def export_inventory_csv(store: Store = Depends(get_store)):
media_type="text/csv",
headers={"Content-Disposition": "attachment; filename=inventory.csv"},
)
@router.get("/json")
async def export_full_json(store: Store = Depends(get_store)):
"""Export full pantry inventory + saved recipes as a single JSON file.
Intended for data portability users can import this into another
Kiwi instance or keep it as an offline backup.
"""
inventory, saved = await asyncio.gather(
asyncio.to_thread(store.list_inventory),
asyncio.to_thread(store.get_saved_recipes),
)
export_doc = {
"kiwi_export": {
"version": "1.0",
"exported_at": datetime.now(timezone.utc).isoformat(),
"inventory": [dict(row) for row in inventory],
"saved_recipes": [dict(row) for row in saved],
}
}
body = json.dumps(export_doc, default=str, indent=2)
filename = f"kiwi-export-{datetime.now(timezone.utc).strftime('%Y%m%d')}.json"
return StreamingResponse(
iter([body]),
media_type="application/json",
headers={"Content-Disposition": f"attachment; filename={filename}"},
)

View file

@ -1,103 +0,0 @@
"""Screenshot attachment endpoint for in-app feedback.
After the cf-core feedback router creates a Forgejo issue, the frontend
can call POST /feedback/attach to upload a screenshot and pin it as a
comment on that issue.
The endpoint is separate from the cf-core router so Kiwi owns it
without modifying shared infrastructure.
"""
from __future__ import annotations
import base64
import os
import requests
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
router = APIRouter()
_FORGEJO_BASE = os.environ.get(
"FORGEJO_API_URL", "https://git.opensourcesolarpunk.com/api/v1"
)
_REPO = "Circuit-Forge/kiwi"
_MAX_BYTES = 5 * 1024 * 1024 # 5 MB
class AttachRequest(BaseModel):
issue_number: int
filename: str = Field(default="screenshot.png", max_length=80)
image_b64: str # data URI or raw base64
class AttachResponse(BaseModel):
comment_url: str
def _forgejo_headers() -> dict[str, str]:
token = os.environ.get("FORGEJO_API_TOKEN", "")
return {"Authorization": f"token {token}"}
def _decode_image(image_b64: str) -> tuple[bytes, str]:
"""Return (raw_bytes, mime_type) from a base64 string or data URI."""
if image_b64.startswith("data:"):
header, _, data = image_b64.partition(",")
mime = header.split(";")[0].split(":")[1] if ":" in header else "image/png"
else:
data = image_b64
mime = "image/png"
return base64.b64decode(data), mime
@router.post("/attach", response_model=AttachResponse)
def attach_screenshot(payload: AttachRequest) -> AttachResponse:
"""Upload a screenshot to a Forgejo issue as a comment with embedded image.
The image is uploaded as an issue asset, then referenced in a comment
so it is visible inline when the issue is viewed.
"""
token = os.environ.get("FORGEJO_API_TOKEN", "")
if not token:
raise HTTPException(status_code=503, detail="Feedback not configured.")
raw_bytes, mime = _decode_image(payload.image_b64)
if len(raw_bytes) > _MAX_BYTES:
raise HTTPException(
status_code=413,
detail=f"Screenshot exceeds 5 MB limit ({len(raw_bytes) // 1024} KB received).",
)
# Upload image as issue asset
asset_resp = requests.post(
f"{_FORGEJO_BASE}/repos/{_REPO}/issues/{payload.issue_number}/assets",
headers=_forgejo_headers(),
files={"attachment": (payload.filename, raw_bytes, mime)},
timeout=20,
)
if not asset_resp.ok:
raise HTTPException(
status_code=502,
detail=f"Forgejo asset upload failed: {asset_resp.text[:200]}",
)
asset_url = asset_resp.json().get("browser_download_url", "")
# Pin as a comment so the image is visible inline
comment_body = f"**Screenshot attached by reporter:**\n\n![screenshot]({asset_url})"
comment_resp = requests.post(
f"{_FORGEJO_BASE}/repos/{_REPO}/issues/{payload.issue_number}/comments",
headers={**_forgejo_headers(), "Content-Type": "application/json"},
json={"body": comment_body},
timeout=15,
)
if not comment_resp.ok:
raise HTTPException(
status_code=502,
detail=f"Forgejo comment failed: {comment_resp.text[:200]}",
)
comment_url = comment_resp.json().get("html_url", "")
return AttachResponse(comment_url=comment_url)

View file

@ -128,18 +128,15 @@ async def household_status(session: CloudUser = Depends(_require_premium)):
@router.post("/invite", response_model=HouseholdInviteResponse)
async def create_invite(session: CloudUser = Depends(_require_household_owner)):
"""Generate a one-time invite token valid for 7 days."""
store = Store(session.db)
token = secrets.token_hex(32)
expires_at = (datetime.now(timezone.utc) + timedelta(days=_INVITE_TTL_DAYS)).isoformat()
store = Store(session.db)
try:
store.conn.execute(
"""INSERT INTO household_invites (token, household_id, created_by, expires_at)
VALUES (?, ?, ?, ?)""",
(token, session.household_id, session.user_id, expires_at),
)
store.conn.commit()
finally:
store.close()
store.conn.execute(
"""INSERT INTO household_invites (token, household_id, created_by, expires_at)
VALUES (?, ?, ?, ?)""",
(token, session.household_id, session.user_id, expires_at),
)
store.conn.commit()
invite_url = f"{_KIWI_BASE_URL}/#/join?household_id={session.household_id}&token={token}"
return HouseholdInviteResponse(token=token, invite_url=invite_url, expires_at=expires_at)
@ -155,27 +152,24 @@ async def accept_invite(
hh_store = _household_store(body.household_id)
now = datetime.now(timezone.utc).isoformat()
try:
row = hh_store.conn.execute(
"""SELECT token, expires_at, used_at FROM household_invites
WHERE token = ? AND household_id = ?""",
(body.token, body.household_id),
).fetchone()
row = hh_store.conn.execute(
"""SELECT token, expires_at, used_at FROM household_invites
WHERE token = ? AND household_id = ?""",
(body.token, body.household_id),
).fetchone()
if not row:
raise HTTPException(status_code=404, detail="Invite not found.")
if row["used_at"] is not None:
raise HTTPException(status_code=410, detail="Invite already used.")
if row["expires_at"] < now:
raise HTTPException(status_code=410, detail="Invite has expired.")
if not row:
raise HTTPException(status_code=404, detail="Invite not found.")
if row["used_at"] is not None:
raise HTTPException(status_code=410, detail="Invite already used.")
if row["expires_at"] < now:
raise HTTPException(status_code=410, detail="Invite has expired.")
hh_store.conn.execute(
"UPDATE household_invites SET used_at = ?, used_by = ? WHERE token = ?",
(now, session.user_id, body.token),
)
hh_store.conn.commit()
finally:
hh_store.close()
hh_store.conn.execute(
"UPDATE household_invites SET used_at = ?, used_by = ? WHERE token = ?",
(now, session.user_id, body.token),
)
hh_store.conn.commit()
_heimdall_post("/admin/household/add-member", {
"household_id": body.household_id,

View file

@ -1,185 +0,0 @@
"""Kiwi — /api/v1/imitate/samples endpoint for Avocet Imitate tab.
Returns the actual assembled prompt Kiwi sends to its LLM for recipe generation,
including the full pantry context (expiry-first ordering), dietary constraints
(from user_settings if present), and the Level 3 format instructions.
"""
from __future__ import annotations
from fastapi import APIRouter, Depends
from app.cloud_session import get_session, CloudUser
from app.db.store import Store
router = APIRouter()
_LEVEL3_FORMAT = [
"",
"Reply using EXACTLY this plain-text format — no markdown, no bold, no extra commentary:",
"Title: <name of the dish>",
"Ingredients: <comma-separated list>",
"Directions:",
"1. <first step>",
"2. <second step>",
"3. <continue for each step>",
"Notes: <optional tips>",
]
_LEVEL4_FORMAT = [
"",
"Reply using EXACTLY this plain-text format — no markdown, no bold:",
"Title: <name of the dish>",
"Ingredients: <comma-separated list>",
"Directions:",
"1. <first step>",
"2. <second step>",
"Notes: <optional tips>",
]
def _read_user_settings(store: Store) -> dict:
"""Read all key/value pairs from user_settings table."""
try:
rows = store.conn.execute("SELECT key, value FROM user_settings").fetchall()
return {r["key"]: r["value"] for r in rows}
except Exception:
return {}
def _build_recipe_prompt(
pantry_names: list[str],
expiring_names: list[str],
constraints: list[str],
allergies: list[str],
level: int = 3,
) -> str:
"""Assemble the recipe generation prompt matching Kiwi's Level 3/4 format."""
# Expiring items first, then remaining pantry items (deduped)
expiring_set = set(expiring_names)
ordered = list(expiring_names) + [n for n in pantry_names if n not in expiring_set]
if not ordered:
ordered = pantry_names
if level == 4:
lines = [
"Surprise me with a creative, unexpected recipe.",
"Only use ingredients that make culinary sense together. "
"Do not force flavoured/sweetened items (vanilla yoghurt, flavoured syrups, jam) into savoury dishes.",
f"Ingredients available: {', '.join(ordered)}",
]
if constraints:
lines.append(f"Constraints: {', '.join(constraints)}")
if allergies:
lines.append(f"Must NOT contain: {', '.join(allergies)}")
lines.append("Treat any mystery ingredient as a wildcard — use your imagination.")
lines += _LEVEL4_FORMAT
else:
lines = [
"You are a creative chef. Generate a recipe using the ingredients below.",
"IMPORTANT: When you use a pantry item, list it in Ingredients using its exact name "
"from the pantry list. Do not add adjectives, quantities, or cooking states "
"(e.g. use 'butter', not 'unsalted butter' or '2 tbsp butter').",
"IMPORTANT: Only use pantry items that make culinary sense for the dish. "
"Do NOT force flavoured/sweetened items (vanilla yoghurt, fruit yoghurt, jam, "
"dessert sauces, flavoured syrups) into savoury dishes.",
"IMPORTANT: Do not default to the same ingredient repeatedly across dishes. "
"If a pantry item does not genuinely improve this specific dish, leave it out.",
"",
f"Pantry items: {', '.join(ordered)}",
]
if expiring_names:
lines.append(
f"Priority — use these soon (expiring): {', '.join(expiring_names)}"
)
if constraints:
lines.append(f"Dietary constraints: {', '.join(constraints)}")
if allergies:
lines.append(f"IMPORTANT — must NOT contain: {', '.join(allergies)}")
lines += _LEVEL3_FORMAT
return "\n".join(lines)
@router.get("/samples")
async def imitate_samples(
limit: int = 5,
level: int = 3,
session: CloudUser = Depends(get_session),
):
"""Return assembled recipe generation prompts for Avocet's Imitate tab.
Each sample includes:
system_prompt empty (Kiwi uses no system context)
input_text full Level 3/4 prompt with pantry items, expiring items,
dietary constraints, and format instructions
output_text empty (no prior LLM output stored per-request)
level: 3 (structured with element biasing context) or 4 (wildcard creative)
limit: max number of distinct prompt variants to return (varies by pantry state)
"""
limit = max(1, min(limit, 10))
store = Store(session.db)
# Full pantry for context
all_items = store.list_inventory()
pantry_names = [r["product_name"] for r in all_items if r.get("product_name")]
# Expiring items as priority ingredients
expiring = store.expiring_soon(days=14)
expiring_names = [r["product_name"] for r in expiring if r.get("product_name")]
# Dietary constraints from user_settings (keys: constraints, allergies)
settings = _read_user_settings(store)
import json as _json
try:
constraints = _json.loads(settings.get("dietary_constraints", "[]")) or []
except Exception:
constraints = []
try:
allergies = _json.loads(settings.get("dietary_allergies", "[]")) or []
except Exception:
allergies = []
if not pantry_names:
return {"samples": [], "total": 0, "type": f"recipe_level{level}"}
# Build prompt variants: one per expiring item as the "anchor" ingredient,
# plus one general pantry prompt. Cap at limit.
samples = []
seen_anchors: set[str] = set()
for item in (expiring[:limit - 1] if expiring else []):
anchor = item.get("product_name", "")
if not anchor or anchor in seen_anchors:
continue
seen_anchors.add(anchor)
# Put this item first in the list for the prompt
ordered_expiring = [anchor] + [n for n in expiring_names if n != anchor]
prompt = _build_recipe_prompt(pantry_names, ordered_expiring, constraints, allergies, level)
samples.append({
"id": item.get("id", 0),
"anchor_item": anchor,
"expiring_count": len(expiring_names),
"pantry_count": len(pantry_names),
"system_prompt": "",
"input_text": prompt,
"output_text": "",
})
# One general prompt using all expiring as priority
if len(samples) < limit:
prompt = _build_recipe_prompt(pantry_names, expiring_names, constraints, allergies, level)
samples.append({
"id": 0,
"anchor_item": "full pantry",
"expiring_count": len(expiring_names),
"pantry_count": len(pantry_names),
"system_prompt": "",
"input_text": prompt,
"output_text": "",
})
return {"samples": samples, "total": len(samples), "type": f"recipe_level{level}"}

View file

@ -3,7 +3,6 @@
from __future__ import annotations
import asyncio
import logging
import uuid
from pathlib import Path
from typing import Any, Dict, List, Optional
@ -12,73 +11,28 @@ import aiofiles
from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile, status
from pydantic import BaseModel
from app.cloud_session import CloudUser, _auth_label, get_session
log = logging.getLogger(__name__)
from app.cloud_session import CloudUser, get_session
from app.db.session import get_store
from app.services.expiration_predictor import ExpirationPredictor
_predictor = ExpirationPredictor()
from app.db.store import Store
from app.models.schemas.inventory import (
BarcodeScanResponse,
BulkAddByNameRequest,
BulkAddByNameResponse,
BulkAddItemResult,
DiscardRequest,
InventoryItemCreate,
InventoryItemResponse,
InventoryItemUpdate,
InventoryStats,
PartialConsumeRequest,
ProductCreate,
ProductResponse,
ProductUpdate,
TagCreate,
TagResponse,
)
from app.models.schemas.label_capture import LabelConfirmRequest
router = APIRouter()
# ── Helpers ───────────────────────────────────────────────────────────────────
def _user_constraints(store) -> list[str]:
"""Load active dietary constraints from user settings (comma-separated string)."""
raw = store.get_setting("dietary_constraints") or ""
return [c.strip() for c in raw.split(",") if c.strip()]
def _enrich_item(item: dict, user_constraints: list[str] | None = None) -> dict:
"""Attach computed fields: opened_expiry_date, secondary_state/uses/warning/discard_signs."""
from datetime import date, timedelta
opened = item.get("opened_date")
if opened:
days = _predictor.days_after_opening(item.get("category"))
if days is not None:
try:
opened_expiry = date.fromisoformat(opened) + timedelta(days=days)
item = {**item, "opened_expiry_date": str(opened_expiry)}
except ValueError:
pass
if "opened_expiry_date" not in item:
item = {**item, "opened_expiry_date": None}
# Secondary use window — check sell-by date (not opened expiry).
# Apply dietary constraint filter (e.g. wine suppressed for halal/alcohol-free).
sec = _predictor.secondary_state(item.get("category"), item.get("expiration_date"))
sec = _predictor.filter_secondary_by_constraints(sec, user_constraints or [])
item = {
**item,
"secondary_state": sec["label"] if sec else None,
"secondary_uses": sec["uses"] if sec else None,
"secondary_warning": sec["warning"] if sec else None,
"secondary_discard_signs": sec["discard_signs"] if sec else None,
}
return item
# ── Products ──────────────────────────────────────────────────────────────────
@router.post("/products", response_model=ProductResponse, status_code=status.HTTP_201_CREATED)
@ -163,12 +117,7 @@ async def delete_product(product_id: int, store: Store = Depends(get_store)):
# ── Inventory items ───────────────────────────────────────────────────────────
@router.post("/items", response_model=InventoryItemResponse, status_code=status.HTTP_201_CREATED)
async def create_inventory_item(
body: InventoryItemCreate,
store: Store = Depends(get_store),
session: CloudUser = Depends(get_session),
):
log.info("add_item auth=%s tier=%s product_id=%s", _auth_label(session.user_id), session.tier, body.product_id)
async def create_inventory_item(body: InventoryItemCreate, store: Store = Depends(get_store)):
item = await asyncio.to_thread(
store.add_inventory_item,
body.product_id,
@ -181,10 +130,7 @@ async def create_inventory_item(
notes=body.notes,
source=body.source,
)
# RETURNING * omits joined columns (product_name, barcode, category).
# Re-fetch with the products JOIN so the response is fully populated (#99).
full_item = await asyncio.to_thread(store.get_inventory_item, item["id"])
return InventoryItemResponse.model_validate(full_item)
return InventoryItemResponse.model_validate(item)
@router.post("/items/bulk-add-by-name", response_model=BulkAddByNameResponse)
@ -197,7 +143,7 @@ async def bulk_add_items_by_name(body: BulkAddByNameRequest, store: Store = Depe
for entry in body.items:
try:
product, _ = await asyncio.to_thread(
store.get_or_create_product, entry.name, None, source="manual"
store.get_or_create_product, entry.name, None, source="shopping"
)
item = await asyncio.to_thread(
store.add_inventory_item,
@ -205,7 +151,7 @@ async def bulk_add_items_by_name(body: BulkAddByNameRequest, store: Store = Depe
entry.location,
quantity=entry.quantity,
unit=entry.unit,
source="manual",
source="shopping",
)
results.append(BulkAddItemResult(name=entry.name, ok=True, item_id=item["id"]))
except Exception as exc:
@ -222,15 +168,13 @@ async def list_inventory_items(
store: Store = Depends(get_store),
):
items = await asyncio.to_thread(store.list_inventory, location, item_status)
constraints = await asyncio.to_thread(_user_constraints, store)
return [InventoryItemResponse.model_validate(_enrich_item(i, constraints)) for i in items]
return [InventoryItemResponse.model_validate(i) for i in items]
@router.get("/items/expiring", response_model=List[InventoryItemResponse])
async def get_expiring_items(days: int = 7, store: Store = Depends(get_store)):
items = await asyncio.to_thread(store.expiring_soon, days)
constraints = await asyncio.to_thread(_user_constraints, store)
return [InventoryItemResponse.model_validate(_enrich_item(i, constraints)) for i in items]
return [InventoryItemResponse.model_validate(i) for i in items]
@router.get("/items/{item_id}", response_model=InventoryItemResponse)
@ -238,8 +182,7 @@ async def get_inventory_item(item_id: int, store: Store = Depends(get_store)):
item = await asyncio.to_thread(store.get_inventory_item, item_id)
if not item:
raise HTTPException(status_code=404, detail="Inventory item not found")
constraints = await asyncio.to_thread(_user_constraints, store)
return InventoryItemResponse.model_validate(_enrich_item(item, constraints))
return InventoryItemResponse.model_validate(item)
@router.patch("/items/{item_id}", response_model=InventoryItemResponse)
@ -251,83 +194,24 @@ async def update_inventory_item(
updates["purchase_date"] = str(updates["purchase_date"])
if "expiration_date" in updates and updates["expiration_date"]:
updates["expiration_date"] = str(updates["expiration_date"])
if "opened_date" in updates and updates["opened_date"]:
updates["opened_date"] = str(updates["opened_date"])
item = await asyncio.to_thread(store.update_inventory_item, item_id, **updates)
if not item:
raise HTTPException(status_code=404, detail="Inventory item not found")
constraints = await asyncio.to_thread(_user_constraints, store)
return InventoryItemResponse.model_validate(_enrich_item(item, constraints))
@router.post("/items/{item_id}/open", response_model=InventoryItemResponse)
async def mark_item_opened(item_id: int, store: Store = Depends(get_store)):
"""Record that this item was opened today, triggering secondary shelf-life tracking."""
from datetime import date
item = await asyncio.to_thread(
store.update_inventory_item,
item_id,
opened_date=str(date.today()),
)
if not item:
raise HTTPException(status_code=404, detail="Inventory item not found")
constraints = await asyncio.to_thread(_user_constraints, store)
return InventoryItemResponse.model_validate(_enrich_item(item, constraints))
return InventoryItemResponse.model_validate(item)
@router.post("/items/{item_id}/consume", response_model=InventoryItemResponse)
async def consume_item(
item_id: int,
body: Optional[PartialConsumeRequest] = None,
store: Store = Depends(get_store),
):
"""Consume an inventory item fully or partially.
When body.quantity is provided, decrements by that amount and only marks
status=consumed when quantity reaches zero. Omit body to consume all.
"""
from datetime import datetime, timezone
now = datetime.now(timezone.utc).isoformat()
if body is not None:
item = await asyncio.to_thread(
store.partial_consume_item, item_id, body.quantity, now
)
else:
item = await asyncio.to_thread(
store.update_inventory_item,
item_id,
status="consumed",
consumed_at=now,
)
if not item:
raise HTTPException(status_code=404, detail="Inventory item not found")
constraints = await asyncio.to_thread(_user_constraints, store)
return InventoryItemResponse.model_validate(_enrich_item(item, constraints))
@router.post("/items/{item_id}/discard", response_model=InventoryItemResponse)
async def discard_item(
item_id: int,
body: DiscardRequest = DiscardRequest(),
store: Store = Depends(get_store),
):
"""Mark an item as discarded (not used, spoiled, etc).
Optional reason field accepts free text or a preset label
('not used', 'spoiled', 'excess', 'other').
"""
async def consume_item(item_id: int, store: Store = Depends(get_store)):
from datetime import datetime, timezone
item = await asyncio.to_thread(
store.update_inventory_item,
item_id,
status="discarded",
status="consumed",
consumed_at=datetime.now(timezone.utc).isoformat(),
disposal_reason=body.reason,
)
if not item:
raise HTTPException(status_code=404, detail="Inventory item not found")
constraints = await asyncio.to_thread(_user_constraints, store)
return InventoryItemResponse.model_validate(_enrich_item(item, constraints))
return InventoryItemResponse.model_validate(item)
@router.delete("/items/{item_id}", status_code=status.HTTP_204_NO_CONTENT)
@ -350,31 +234,6 @@ class BarcodeScanTextRequest(BaseModel):
auto_add_to_inventory: bool = True
def _captured_to_product_info(row: dict) -> dict:
"""Convert a captured_products row to the product_info dict shape used by
the barcode scan flow (mirrors what OpenFoodFactsService returns)."""
macros: dict = {}
for field in ("calories", "fat_g", "saturated_fat_g", "carbs_g", "sugar_g",
"fiber_g", "protein_g", "sodium_mg", "serving_size_g"):
if row.get(field) is not None:
macros[field] = row[field]
return {
"name": row.get("product_name") or row.get("barcode", "Unknown Product"),
"brand": row.get("brand"),
"category": None,
"nutrition_data": macros,
"ingredient_names": row.get("ingredient_names") or [],
"allergens": row.get("allergens") or [],
"source": "visual_capture",
}
def _gap_message(tier: str, has_visual_capture: bool) -> str:
if has_visual_capture:
return "We couldn't find this product. Photograph the nutrition label to add it."
return "Not found in any product database — add manually"
@router.post("/scan/text", response_model=BarcodeScanResponse)
async def scan_barcode_text(
body: BarcodeScanTextRequest,
@ -382,24 +241,12 @@ async def scan_barcode_text(
session: CloudUser = Depends(get_session),
):
"""Scan a barcode from a text string (e.g. from a hardware scanner or manual entry)."""
log.info("scan auth=%s tier=%s barcode=%r", _auth_label(session.user_id), session.tier, body.barcode)
from app.services.openfoodfacts import OpenFoodFactsService
from app.services.expiration_predictor import ExpirationPredictor
from app.tiers import can_use
off = OpenFoodFactsService()
predictor = ExpirationPredictor()
has_visual_capture = can_use("visual_label_capture", session.tier, session.has_byok)
# 1. Check local captured-products cache before hitting FDC/OFF
cached = await asyncio.to_thread(store.get_captured_product, body.barcode)
if cached and cached.get("confirmed_by_user"):
product_info: dict | None = _captured_to_product_info(cached)
product_source = "visual_capture"
else:
off = OpenFoodFactsService()
product_info = await off.lookup_product(body.barcode)
product_source = "openfoodfacts"
product_info = await off.lookup_product(body.barcode)
inventory_item = None
if product_info and body.auto_add_to_inventory:
@ -410,7 +257,7 @@ async def scan_barcode_text(
brand=product_info.get("brand"),
category=product_info.get("category"),
nutrition_data=product_info.get("nutrition_data", {}),
source=product_source,
source="openfoodfacts",
source_data=product_info,
)
exp = predictor.predict_expiration(
@ -420,14 +267,10 @@ async def scan_barcode_text(
tier=session.tier,
has_byok=session.has_byok,
)
# Use OFFs pack size when detected; caller-supplied quantity is a fallback
resolved_qty = product_info.get("pack_quantity") or body.quantity
resolved_unit = product_info.get("pack_unit") or "count"
inventory_item = await asyncio.to_thread(
store.add_inventory_item,
product["id"], body.location,
quantity=resolved_qty,
unit=resolved_unit,
quantity=body.quantity,
expiration_date=str(exp) if exp else None,
source="barcode_scan",
)
@ -435,8 +278,6 @@ async def scan_barcode_text(
else:
result_product = None
product_found = product_info is not None
needs_capture = not product_found and has_visual_capture
return BarcodeScanResponse(
success=True,
barcodes_found=1,
@ -446,9 +287,7 @@ async def scan_barcode_text(
"product": result_product,
"inventory_item": InventoryItemResponse.model_validate(inventory_item) if inventory_item else None,
"added_to_inventory": inventory_item is not None,
"needs_manual_entry": not product_found and not needs_capture,
"needs_visual_capture": needs_capture,
"message": "Added to inventory" if inventory_item else _gap_message(session.tier, needs_capture),
"message": "Added to inventory" if inventory_item else "Product not found in database",
}],
message="Barcode processed",
)
@ -464,10 +303,6 @@ async def scan_barcode_image(
session: CloudUser = Depends(get_session),
):
"""Scan a barcode from an uploaded image. Requires Phase 2 scanner integration."""
log.info("scan_image auth=%s tier=%s", _auth_label(session.user_id), session.tier)
from app.tiers import can_use
has_visual_capture = can_use("visual_label_capture", session.tier, session.has_byok)
temp_dir = Path("/tmp/kiwi_barcode_scans")
temp_dir.mkdir(parents=True, exist_ok=True)
temp_file = temp_dir / f"{uuid.uuid4()}_{file.filename}"
@ -490,16 +325,7 @@ async def scan_barcode_image(
results = []
for bc in barcodes:
code = bc["data"]
# Check local visual-capture cache before hitting FDC/OFF
cached = await asyncio.to_thread(store.get_captured_product, code)
if cached and cached.get("confirmed_by_user"):
product_info: dict | None = _captured_to_product_info(cached)
product_source = "visual_capture"
else:
product_info = await off.lookup_product(code)
product_source = "openfoodfacts"
product_info = await off.lookup_product(code)
inventory_item = None
if product_info and auto_add_to_inventory:
product, _ = await asyncio.to_thread(
@ -509,7 +335,7 @@ async def scan_barcode_image(
brand=product_info.get("brand"),
category=product_info.get("category"),
nutrition_data=product_info.get("nutrition_data", {}),
source=product_source,
source="openfoodfacts",
source_data=product_info,
)
exp = predictor.predict_expiration(
@ -517,29 +343,22 @@ async def scan_barcode_image(
location,
product_name=product_info.get("name", code),
tier=session.tier,
has_byok=session.has_byok,
has_byok=session.has_byok,
)
resolved_qty = product_info.get("pack_quantity") or quantity
resolved_unit = product_info.get("pack_unit") or "count"
inventory_item = await asyncio.to_thread(
store.add_inventory_item,
product["id"], location,
quantity=resolved_qty,
unit=resolved_unit,
quantity=quantity,
expiration_date=str(exp) if exp else None,
source="barcode_scan",
)
product_found = product_info is not None
needs_capture = not product_found and has_visual_capture
results.append({
"barcode": code,
"barcode_type": bc.get("type", "unknown"),
"product": ProductResponse.model_validate(product_info) if product_info else None,
"product": ProductResponse.model_validate(product) if product_info else None,
"inventory_item": InventoryItemResponse.model_validate(inventory_item) if inventory_item else None,
"added_to_inventory": inventory_item is not None,
"needs_manual_entry": not product_found and not needs_capture,
"needs_visual_capture": needs_capture,
"message": "Added to inventory" if inventory_item else _gap_message(session.tier, needs_capture),
"message": "Added to inventory" if inventory_item else "Barcode scanned",
})
return BarcodeScanResponse(
success=True, barcodes_found=len(barcodes), results=results,
@ -550,143 +369,6 @@ async def scan_barcode_image(
temp_file.unlink()
# ── Visual label capture (kiwi#79) ────────────────────────────────────────────
@router.post("/scan/label-capture")
async def capture_nutrition_label(
file: UploadFile = File(...),
barcode: str = Form(...),
store: Store = Depends(get_store),
session: CloudUser = Depends(get_session),
):
"""Photograph a nutrition label for an unenriched product (paid tier).
Sends the image to the vision model and returns structured nutrition data
for user review. Fields extracted with confidence < 0.7 should be
highlighted in amber in the UI.
"""
from app.tiers import can_use
from app.models.schemas.label_capture import LabelCaptureResponse
from app.services.label_capture import extract_label, needs_review as _needs_review
if not can_use("visual_label_capture", session.tier, session.has_byok):
raise HTTPException(status_code=403, detail="Visual label capture requires a Paid tier or higher.")
log.info("label_capture tier=%s barcode=%r", session.tier, barcode)
image_bytes = await file.read()
extraction = await asyncio.to_thread(extract_label, image_bytes)
return LabelCaptureResponse(
barcode=barcode,
product_name=extraction.get("product_name"),
brand=extraction.get("brand"),
serving_size_g=extraction.get("serving_size_g"),
calories=extraction.get("calories"),
fat_g=extraction.get("fat_g"),
saturated_fat_g=extraction.get("saturated_fat_g"),
carbs_g=extraction.get("carbs_g"),
sugar_g=extraction.get("sugar_g"),
fiber_g=extraction.get("fiber_g"),
protein_g=extraction.get("protein_g"),
sodium_mg=extraction.get("sodium_mg"),
ingredient_names=extraction.get("ingredient_names") or [],
allergens=extraction.get("allergens") or [],
confidence=extraction.get("confidence", 0.0),
needs_review=_needs_review(extraction),
)
@router.post("/scan/label-confirm")
async def confirm_nutrition_label(
body: LabelConfirmRequest,
store: Store = Depends(get_store),
session: CloudUser = Depends(get_session),
):
"""Confirm and save a user-reviewed label extraction.
Saves the product to the local cache so future scans of the same barcode
resolve instantly without another capture. Optionally adds the item to
the user's inventory.
"""
from app.tiers import can_use
from app.models.schemas.label_capture import LabelConfirmResponse
from app.services.expiration_predictor import ExpirationPredictor
if not can_use("visual_label_capture", session.tier, session.has_byok):
raise HTTPException(status_code=403, detail="Visual label capture requires a Paid tier or higher.")
log.info("label_confirm tier=%s barcode=%r", session.tier, body.barcode)
# Persist to local visual-capture cache
await asyncio.to_thread(
store.save_captured_product,
body.barcode,
product_name=body.product_name,
brand=body.brand,
serving_size_g=body.serving_size_g,
calories=body.calories,
fat_g=body.fat_g,
saturated_fat_g=body.saturated_fat_g,
carbs_g=body.carbs_g,
sugar_g=body.sugar_g,
fiber_g=body.fiber_g,
protein_g=body.protein_g,
sodium_mg=body.sodium_mg,
ingredient_names=body.ingredient_names,
allergens=body.allergens,
confidence=body.confidence,
confirmed_by_user=True,
)
product_id: int | None = None
inventory_item_id: int | None = None
if body.auto_add:
predictor = ExpirationPredictor()
nutrition = {}
for field in ("calories", "fat_g", "saturated_fat_g", "carbs_g", "sugar_g",
"fiber_g", "protein_g", "sodium_mg", "serving_size_g"):
val = getattr(body, field, None)
if val is not None:
nutrition[field] = val
product, _ = await asyncio.to_thread(
store.get_or_create_product,
body.product_name or body.barcode,
body.barcode,
brand=body.brand,
category=None,
nutrition_data=nutrition,
source="visual_capture",
source_data={},
)
product_id = product["id"]
exp = predictor.predict_expiration(
"",
body.location,
product_name=body.product_name or body.barcode,
tier=session.tier,
has_byok=session.has_byok,
)
inv_item = await asyncio.to_thread(
store.add_inventory_item,
product_id, body.location,
quantity=body.quantity,
unit="count",
expiration_date=str(exp) if exp else None,
source="visual_capture",
)
inventory_item_id = inv_item["id"]
return LabelConfirmResponse(
ok=True,
barcode=body.barcode,
product_id=product_id,
inventory_item_id=inventory_item_id,
message="Product saved" + (" and added to inventory" if body.auto_add else ""),
)
# ── Tags ──────────────────────────────────────────────────────────────────────
@router.post("/tags", response_model=TagResponse, status_code=status.HTTP_201_CREATED)

View file

@ -19,7 +19,6 @@ from app.models.schemas.meal_plan import (
PrepTaskSummary,
ShoppingListResponse,
SlotSummary,
UpdatePlanRequest,
UpdatePrepTaskRequest,
UpsertSlotRequest,
VALID_MEAL_TYPES,
@ -82,21 +81,13 @@ async def create_plan(
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
) -> PlanSummary:
import sqlite3
# Free tier is locked to dinner-only; paid+ may configure meal types
if can_use("meal_plan_config", session.tier):
meal_types = [t for t in req.meal_types if t in VALID_MEAL_TYPES] or ["dinner"]
else:
meal_types = ["dinner"]
try:
plan = await asyncio.to_thread(store.create_meal_plan, str(req.week_start), meal_types)
except sqlite3.IntegrityError:
raise HTTPException(
status_code=409,
detail=f"A meal plan for the week of {req.week_start} already exists.",
)
plan = await asyncio.to_thread(store.create_meal_plan, str(req.week_start), meal_types)
slots = await asyncio.to_thread(store.get_plan_slots, plan["id"])
return _plan_summary(plan, slots)
@ -114,28 +105,6 @@ async def list_plans(
return result
@router.patch("/{plan_id}", response_model=PlanSummary)
async def update_plan(
plan_id: int,
req: UpdatePlanRequest,
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
) -> PlanSummary:
plan = await asyncio.to_thread(store.get_meal_plan, plan_id)
if plan is None:
raise HTTPException(status_code=404, detail="Plan not found.")
# Free tier stays dinner-only; paid+ may add meal types
if can_use("meal_plan_config", session.tier):
meal_types = [t for t in req.meal_types if t in VALID_MEAL_TYPES] or ["dinner"]
else:
meal_types = ["dinner"]
updated = await asyncio.to_thread(store.update_meal_plan_types, plan_id, meal_types)
if updated is None:
raise HTTPException(status_code=404, detail="Plan not found.")
slots = await asyncio.to_thread(store.get_plan_slots, plan_id)
return _plan_summary(updated, slots)
@router.get("/{plan_id}", response_model=PlanSummary)
async def get_plan(
plan_id: int,

View file

@ -219,7 +219,7 @@ def _commit_items(
receipt_id=receipt_id,
purchase_date=str(purchase_date) if purchase_date else None,
expiration_date=str(exp) if exp else None,
source="receipt",
source="receipt_ocr",
)
created.append(ApprovedInventoryItem(

View file

@ -1,27 +0,0 @@
"""Proxy endpoint: exposes cf-orch call budget to the Kiwi frontend.
Only lifetime/founders users have a license_key subscription and free
users receive null (no budget UI shown).
"""
from __future__ import annotations
from fastapi import APIRouter, Depends
from app.cloud_session import CloudUser, get_session
from app.services.heimdall_orch import get_orch_usage
router = APIRouter()
@router.get("")
async def orch_usage_endpoint(
session: CloudUser = Depends(get_session),
) -> dict | None:
"""Return the current period's orch usage for the authenticated user.
Returns null if the user has no lifetime/founders license key (i.e. they
are on a subscription or free plan no budget cap applies to them).
"""
if session.license_key is None:
return None
return get_orch_usage(session.license_key, "kiwi")

View file

@ -42,11 +42,9 @@ async def upload_receipt(
)
# Only queue OCR if the feature is enabled server-side AND the user's tier allows it.
# Check tier here, not inside the background task — once dispatched it can't be cancelled.
# Pass session.db (a Path) rather than store — the store dependency closes before
# background tasks run, so the task opens its own store from the DB path.
ocr_allowed = settings.ENABLE_OCR and can_use("receipt_ocr", session.tier, session.has_byok)
if ocr_allowed:
background_tasks.add_task(_process_receipt_ocr, receipt["id"], saved, session.db)
background_tasks.add_task(_process_receipt_ocr, receipt["id"], saved, store)
return ReceiptResponse.model_validate(receipt)
@ -66,7 +64,7 @@ async def upload_receipts_batch(
store.create_receipt, file.filename, str(saved)
)
if ocr_allowed:
background_tasks.add_task(_process_receipt_ocr, receipt["id"], saved, session.db)
background_tasks.add_task(_process_receipt_ocr, receipt["id"], saved, store)
results.append(ReceiptResponse.model_validate(receipt))
return results
@ -99,13 +97,8 @@ async def get_receipt_quality(receipt_id: int, store: Store = Depends(get_store)
return QualityAssessment.model_validate(qa)
async def _process_receipt_ocr(receipt_id: int, image_path: Path, db_path: Path) -> None:
"""Background task: run OCR pipeline on an uploaded receipt.
Accepts db_path (not a Store instance) because FastAPI closes the request-scoped
store before background tasks execute. This task owns its store lifecycle.
"""
store = Store(db_path)
async def _process_receipt_ocr(receipt_id: int, image_path: Path, store: Store) -> None:
"""Background task: run OCR pipeline on an uploaded receipt."""
try:
await asyncio.to_thread(store.update_receipt_status, receipt_id, "processing")
from app.services.receipt_service import ReceiptService
@ -115,5 +108,3 @@ async def _process_receipt_ocr(receipt_id: int, image_path: Path, db_path: Path)
await asyncio.to_thread(
store.update_receipt_status, receipt_id, "error", str(exc)
)
finally:
store.close()

View file

@ -1,166 +0,0 @@
# app/api/endpoints/recipe_tags.py
"""Community subcategory tagging for corpus recipes.
Users can tag a recipe they're viewing with a domain/category/subcategory
from the browse taxonomy. Tags require a community pseudonym and reach
public visibility once two independent users have tagged the same recipe
to the same location (upvotes >= 2).
All tiers may submit and upvote tags community contribution is free.
"""
from __future__ import annotations
import logging
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from app.api.endpoints.community import _get_community_store
from app.api.endpoints.session import get_session
from app.cloud_session import CloudUser
from app.services.recipe.browser_domains import DOMAINS
logger = logging.getLogger(__name__)
router = APIRouter()
ACCEPT_THRESHOLD = 2
# ── Request / response models ──────────────────────────────────────────────────
class TagSubmitBody(BaseModel):
recipe_id: int
domain: str
category: str
subcategory: str | None = None
pseudonym: str
class TagResponse(BaseModel):
id: int
recipe_id: int
domain: str
category: str
subcategory: str | None
pseudonym: str
upvotes: int
accepted: bool
def _to_response(row: dict) -> TagResponse:
return TagResponse(
id=row["id"],
recipe_id=int(row["recipe_ref"]),
domain=row["domain"],
category=row["category"],
subcategory=row.get("subcategory"),
pseudonym=row["pseudonym"],
upvotes=row["upvotes"],
accepted=row["upvotes"] >= ACCEPT_THRESHOLD,
)
def _validate_location(domain: str, category: str, subcategory: str | None) -> None:
"""Raise 422 if (domain, category, subcategory) isn't in the known taxonomy."""
if domain not in DOMAINS:
raise HTTPException(status_code=422, detail=f"Unknown domain '{domain}'.")
cats = DOMAINS[domain].get("categories", {})
if category not in cats:
raise HTTPException(
status_code=422,
detail=f"Unknown category '{category}' in domain '{domain}'.",
)
if subcategory is not None:
subcats = cats[category].get("subcategories", {})
if subcategory not in subcats:
raise HTTPException(
status_code=422,
detail=f"Unknown subcategory '{subcategory}' in '{domain}/{category}'.",
)
# ── Endpoints ──────────────────────────────────────────────────────────────────
@router.get("/recipes/community-tags/{recipe_id}", response_model=list[TagResponse])
async def list_recipe_tags(
recipe_id: int,
session: CloudUser = Depends(get_session),
) -> list[TagResponse]:
"""Return all community tags for a corpus recipe, accepted ones first."""
store = _get_community_store()
if store is None:
return []
tags = store.list_tags_for_recipe(recipe_id)
return [_to_response(r) for r in tags]
@router.post("/recipes/community-tags", response_model=TagResponse, status_code=201)
async def submit_recipe_tag(
body: TagSubmitBody,
session: CloudUser = Depends(get_session),
) -> TagResponse:
"""Tag a corpus recipe with a browse taxonomy location.
Requires the user to have a community pseudonym set. Returns 409 if this
user has already tagged this recipe to this exact location.
"""
store = _get_community_store()
if store is None:
raise HTTPException(
status_code=503,
detail="Community features are not available on this instance.",
)
_validate_location(body.domain, body.category, body.subcategory)
try:
import psycopg2.errors # type: ignore[import]
row = store.submit_recipe_tag(
recipe_id=body.recipe_id,
domain=body.domain,
category=body.category,
subcategory=body.subcategory,
pseudonym=body.pseudonym,
)
return _to_response(row)
except Exception as exc:
if "unique" in str(exc).lower() or "UniqueViolation" in type(exc).__name__:
raise HTTPException(
status_code=409,
detail="You have already tagged this recipe to this location.",
)
logger.error("submit_recipe_tag failed: %s", exc)
raise HTTPException(status_code=500, detail="Failed to submit tag.")
@router.post("/recipes/community-tags/{tag_id}/upvote", response_model=TagResponse)
async def upvote_recipe_tag(
tag_id: int,
pseudonym: str,
session: CloudUser = Depends(get_session),
) -> TagResponse:
"""Upvote an existing community tag.
Returns 409 if this pseudonym has already voted on this tag.
Returns 404 if the tag doesn't exist.
"""
store = _get_community_store()
if store is None:
raise HTTPException(status_code=503, detail="Community features unavailable.")
tag_row = store.get_recipe_tag_by_id(tag_id)
if tag_row is None:
raise HTTPException(status_code=404, detail=f"Tag {tag_id} not found.")
try:
new_upvotes = store.upvote_recipe_tag(tag_id, pseudonym)
except ValueError:
raise HTTPException(status_code=404, detail=f"Tag {tag_id} not found.")
except Exception as exc:
if "unique" in str(exc).lower() or "UniqueViolation" in type(exc).__name__:
raise HTTPException(status_code=409, detail="You have already voted on this tag.")
logger.error("upvote_recipe_tag failed: %s", exc)
raise HTTPException(status_code=500, detail="Failed to upvote tag.")
tag_row["upvotes"] = new_upvotes
return _to_response(tag_row)

View file

@ -2,48 +2,21 @@
from __future__ import annotations
import asyncio
import logging
from pathlib import Path
from typing import Annotated
from fastapi import APIRouter, Depends, HTTPException, Query
from app.cloud_session import CloudUser, _auth_label, get_session
log = logging.getLogger(__name__)
from app.db.session import get_store
from app.cloud_session import CloudUser, get_session
from app.db.store import Store
from app.models.schemas.recipe import (
AssemblyTemplateOut,
BuildRequest,
RecipeJobStatus,
RecipeRequest,
RecipeResult,
RecipeSuggestion,
RoleCandidatesResponse,
StreamTokenRequest,
StreamTokenResponse,
)
from app.services.coordinator_proxy import CoordinatorError, coordinator_authorize
from app.api.endpoints.imitate import _build_recipe_prompt
from app.services.recipe.assembly_recipes import (
build_from_selection,
get_role_candidates,
get_templates_for_api,
)
from app.models.schemas.recipe import RecipeRequest, RecipeResult
from app.services.recipe.browser_domains import (
DOMAINS,
category_has_subcategories,
get_category_names,
get_domain_labels,
get_keywords_for_category,
get_keywords_for_subcategory,
get_subcategory_names,
)
from app.services.recipe.recipe_engine import RecipeEngine
from app.services.recipe.time_effort import parse_time_effort
from app.services.recipe.sensory import build_sensory_exclude
from app.services.heimdall_orch import check_orch_budget
from app.tiers import can_use
router = APIRouter()
@ -64,93 +37,13 @@ def _suggest_in_thread(db_path: Path, req: RecipeRequest) -> RecipeResult:
store.close()
def _build_stream_prompt(db_path: Path, level: int) -> str:
"""Fetch pantry + user settings from DB and build the recipe prompt.
Runs in a thread (called via asyncio.to_thread) so it can use sync Store.
"""
import datetime
store = Store(db_path)
try:
items = store.list_inventory(status="available")
pantry_names = [i["product_name"] for i in items if i.get("product_name")]
today = datetime.date.today()
expiring_names = [
i["product_name"]
for i in items
if i.get("product_name")
and i.get("expiry_date")
and (datetime.date.fromisoformat(i["expiry_date"]) - today).days <= 3
]
settings: dict = {}
try:
rows = store.conn.execute("SELECT key, value FROM user_settings").fetchall()
settings = {r["key"]: r["value"] for r in rows}
except Exception:
pass
constraints_raw = settings.get("dietary_constraints", "")
constraints = [c.strip() for c in constraints_raw.split(",") if c.strip()] if constraints_raw else []
allergies_raw = settings.get("allergies", "")
allergies = [a.strip() for a in allergies_raw.split(",") if a.strip()] if allergies_raw else []
return _build_recipe_prompt(pantry_names, expiring_names, constraints, allergies, level)
finally:
store.close()
async def _enqueue_recipe_job(session: CloudUser, req: RecipeRequest):
"""Queue an async recipe_llm job and return 202 with job_id.
Falls back to synchronous generation in CLOUD_MODE (scheduler polls only
the shared settings DB, not per-user DBs see snipe#45 / kiwi backlog).
"""
import json
import uuid
from fastapi.responses import JSONResponse
from app.cloud_session import CLOUD_MODE
from app.tasks.runner import insert_task
if CLOUD_MODE:
log.warning("recipe_llm async jobs not supported in CLOUD_MODE — falling back to sync")
result = await asyncio.to_thread(_suggest_in_thread, session.db, req)
return result
job_id = f"rec_{uuid.uuid4().hex}"
def _create(db_path: Path) -> int:
store = Store(db_path)
try:
row = store.create_recipe_job(job_id, session.user_id, req.model_dump_json())
return row["id"]
finally:
store.close()
int_id = await asyncio.to_thread(_create, session.db)
params_json = json.dumps({"job_id": job_id})
task_id, is_new = insert_task(session.db, "recipe_llm", int_id, params=params_json)
if is_new:
from app.tasks.scheduler import get_scheduler
get_scheduler(session.db).enqueue(task_id, "recipe_llm", int_id, params_json)
return JSONResponse(content={"job_id": job_id, "status": "queued"}, status_code=202)
@router.post("/suggest")
@router.post("/suggest", response_model=RecipeResult)
async def suggest_recipes(
req: RecipeRequest,
async_mode: bool = Query(default=False, alias="async"),
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
):
log.info("recipes auth=%s tier=%s level=%s", _auth_label(session.user_id), session.tier, req.level)
) -> RecipeResult:
# Inject session-authoritative tier/byok immediately — client-supplied values are ignored.
# Also read stored unit_system preference; default to metric if not set.
unit_system = store.get_setting("unit_system") or "metric"
req = req.model_copy(update={"tier": session.tier, "has_byok": session.has_byok, "unit_system": unit_system})
req = req.model_copy(update={"tier": session.tier, "has_byok": session.has_byok})
if req.level == 4 and not req.wildcard_confirmed:
raise HTTPException(
status_code=400,
@ -163,98 +56,7 @@ async def suggest_recipes(
)
if req.style_id and not can_use("style_picker", req.tier):
raise HTTPException(status_code=403, detail="Style picker requires Paid tier.")
# Orch budget check for lifetime/founders keys — downgrade to L2 (local) if exhausted.
# Subscription and local/BYOK users skip this check entirely.
orch_fallback = False
if (
req.level in (3, 4)
and session.license_key is not None
and not session.has_byok
and session.tier != "local"
):
budget = check_orch_budget(session.license_key, "kiwi")
if not budget.get("allowed", True):
req = req.model_copy(update={"level": 2})
orch_fallback = True
if req.level in (3, 4) and async_mode:
return await _enqueue_recipe_job(session, req)
result = await asyncio.to_thread(_suggest_in_thread, session.db, req)
if orch_fallback:
result = result.model_copy(update={"orch_fallback": True})
return result
@router.post("/stream-token", response_model=StreamTokenResponse)
async def get_stream_token(
req: StreamTokenRequest,
session: CloudUser = Depends(get_session),
) -> StreamTokenResponse:
"""Issue a one-time stream token for LLM recipe generation.
Tier-gated (Paid or BYOK). Builds the prompt from pantry + user settings,
then calls the cf-orch coordinator to obtain a stream URL. Returns
immediately the frontend opens EventSource to the stream URL directly.
"""
if not can_use("recipe_suggestions", session.tier, session.has_byok):
raise HTTPException(
status_code=403,
detail="Streaming recipe generation requires Paid tier or a configured LLM backend.",
)
if req.level == 4 and not req.wildcard_confirmed:
raise HTTPException(
status_code=400,
detail="Level 4 (Wildcard) streaming requires wildcard_confirmed=true.",
)
prompt = await asyncio.to_thread(_build_stream_prompt, session.db, req.level)
try:
result = await coordinator_authorize(prompt=prompt, caller="kiwi-recipe", ttl_s=300)
except CoordinatorError as exc:
raise HTTPException(status_code=exc.status_code, detail=str(exc))
return StreamTokenResponse(
stream_url=result.stream_url,
token=result.token,
expires_in_s=result.expires_in_s,
)
@router.get("/jobs/{job_id}", response_model=RecipeJobStatus)
async def get_recipe_job_status(
job_id: str,
session: CloudUser = Depends(get_session),
) -> RecipeJobStatus:
"""Poll the status of an async recipe generation job.
Returns 404 when job_id is unknown or belongs to a different user.
On status='done' with suggestions=[], the LLM returned empty client
should show a 'no recipe generated, try again' message.
"""
def _get(db_path: Path) -> dict | None:
store = Store(db_path)
try:
return store.get_recipe_job(job_id, session.user_id)
finally:
store.close()
row = await asyncio.to_thread(_get, session.db)
if row is None:
raise HTTPException(status_code=404, detail="Job not found.")
result = None
if row["status"] == "done" and row["result"]:
result = RecipeResult.model_validate_json(row["result"])
return RecipeJobStatus(
job_id=row["job_id"],
status=row["status"],
result=result,
error=row["error"],
)
return await asyncio.to_thread(_suggest_in_thread, session.db, req)
@router.get("/browse/domains")
@ -274,42 +76,15 @@ async def list_browse_categories(
if domain not in DOMAINS:
raise HTTPException(status_code=404, detail=f"Unknown domain '{domain}'.")
cat_names = get_category_names(domain)
keywords_by_category = {cat: get_keywords_for_category(domain, cat) for cat in cat_names}
has_subs = {cat: category_has_subcategories(domain, cat) for cat in cat_names}
def _get(db_path: Path) -> list[dict]:
store = Store(db_path)
try:
return store.get_browser_categories(domain, keywords_by_category, has_subs)
finally:
store.close()
return await asyncio.to_thread(_get, session.db)
@router.get("/browse/{domain}/{category}/subcategories")
async def list_browse_subcategories(
domain: str,
category: str,
session: CloudUser = Depends(get_session),
) -> list[dict]:
"""Return [{subcategory, recipe_count}] for a category that supports subcategories."""
if domain not in DOMAINS:
raise HTTPException(status_code=404, detail=f"Unknown domain '{domain}'.")
if not category_has_subcategories(domain, category):
return []
subcat_names = get_subcategory_names(domain, category)
keywords_by_subcat = {
sub: get_keywords_for_subcategory(domain, category, sub)
for sub in subcat_names
keywords_by_category = {
cat: get_keywords_for_category(domain, cat)
for cat in get_category_names(domain)
}
def _get(db_path: Path) -> list[dict]:
store = Store(db_path)
try:
return store.get_browser_subcategories(domain, keywords_by_subcat)
return store.get_browser_categories(domain, keywords_by_category)
finally:
store.close()
@ -323,37 +98,22 @@ async def browse_recipes(
page: Annotated[int, Query(ge=1)] = 1,
page_size: Annotated[int, Query(ge=1, le=100)] = 20,
pantry_items: Annotated[str | None, Query()] = None,
subcategory: Annotated[str | None, Query()] = None,
q: Annotated[str | None, Query(max_length=200)] = None,
sort: Annotated[str, Query(pattern="^(default|alpha|alpha_desc|match)$")] = "default",
session: CloudUser = Depends(get_session),
) -> dict:
"""Return a paginated list of recipes for a domain/category.
Pass pantry_items as a comma-separated string to receive match_pct badges.
Pass subcategory to narrow within a category that has subcategories.
Pass q to filter by title substring. Pass sort for ordering (default/alpha/alpha_desc/match).
sort=match orders by pantry coverage DESC; falls back to default when no pantry_items.
Pass pantry_items as a comma-separated string to receive match_pct
badges on each result.
"""
if domain not in DOMAINS:
raise HTTPException(status_code=404, detail=f"Unknown domain '{domain}'.")
if category == "_all":
keywords = None # unfiltered browse
elif subcategory:
keywords = get_keywords_for_subcategory(domain, category, subcategory)
if not keywords:
raise HTTPException(
status_code=404,
detail=f"Unknown subcategory '{subcategory}' in '{category}'.",
)
else:
keywords = get_keywords_for_category(domain, category)
if not keywords:
raise HTTPException(
status_code=404,
detail=f"Unknown category '{category}' in domain '{domain}'.",
)
keywords = get_keywords_for_category(domain, category)
if not keywords:
raise HTTPException(
status_code=404,
detail=f"Unknown category '{category}' in domain '{domain}'.",
)
pantry_list = (
[p.strip() for p in pantry_items.split(",") if p.strip()]
@ -364,81 +124,12 @@ async def browse_recipes(
def _browse(db_path: Path) -> dict:
store = Store(db_path)
try:
# Load sensory preferences
sensory_prefs_json = store.get_setting("sensory_preferences")
sensory_exclude = build_sensory_exclude(sensory_prefs_json)
result = store.browse_recipes(
keywords=keywords,
page=page,
page_size=page_size,
pantry_items=pantry_list,
q=q or None,
sort=sort,
sensory_exclude=sensory_exclude,
)
# ── Attach time/effort signals to each browse result ────────────────
import json as _json
for recipe_row in result.get("recipes", []):
directions_raw = recipe_row.get("directions") or []
if isinstance(directions_raw, str):
try:
directions_raw = _json.loads(directions_raw)
except Exception:
directions_raw = []
if directions_raw:
_profile = parse_time_effort(directions_raw)
recipe_row["active_min"] = _profile.active_min
recipe_row["passive_min"] = _profile.passive_min
else:
recipe_row["active_min"] = None
recipe_row["passive_min"] = None
# Remove directions from browse payload — not needed by the card UI
recipe_row.pop("directions", None)
# Community tag fallback: if FTS returned nothing for a subcategory,
# check whether accepted community tags exist for this location and
# fetch those corpus recipes directly by ID.
if result["total"] == 0 and subcategory and keywords:
try:
from app.api.endpoints.community import _get_community_store
cs = _get_community_store()
if cs is not None:
community_ids = cs.get_accepted_recipe_ids_for_subcategory(
domain=domain,
category=category,
subcategory=subcategory,
)
if community_ids:
offset = (page - 1) * page_size
paged_ids = community_ids[offset: offset + page_size]
recipes = store.fetch_recipes_by_ids(paged_ids, pantry_list)
import json as _json_c
for recipe_row in recipes:
directions_raw = recipe_row.get("directions") or []
if isinstance(directions_raw, str):
try:
directions_raw = _json_c.loads(directions_raw)
except Exception:
directions_raw = []
if directions_raw:
_profile = parse_time_effort(directions_raw)
recipe_row["active_min"] = _profile.active_min
recipe_row["passive_min"] = _profile.passive_min
else:
recipe_row["active_min"] = None
recipe_row["passive_min"] = None
recipe_row.pop("directions", None)
result = {
"recipes": recipes,
"total": len(community_ids),
"page": page,
"community_tagged": True,
}
except Exception as exc:
logger.warning("community tag fallback failed: %s", exc)
store.log_browser_telemetry(
domain=domain,
category=category,
@ -452,96 +143,6 @@ async def browse_recipes(
return await asyncio.to_thread(_browse, session.db)
@router.get("/templates", response_model=list[AssemblyTemplateOut])
async def list_assembly_templates() -> list[dict]:
"""Return all 13 assembly templates with ordered role sequences.
Cache-friendly: static data, no per-user state.
"""
return get_templates_for_api()
@router.get("/template-candidates", response_model=RoleCandidatesResponse)
async def get_template_role_candidates(
template_id: str = Query(..., description="Template slug, e.g. 'burrito_taco'"),
role: str = Query(..., description="Role display name, e.g. 'protein'"),
prior_picks: str = Query(default="", description="Comma-separated prior selections"),
session: CloudUser = Depends(get_session),
) -> dict:
"""Return pantry-matched candidates for one wizard step."""
def _get(db_path: Path) -> dict:
store = Store(db_path)
try:
items = store.list_inventory(status="available")
pantry_set = {
item["product_name"]
for item in items
if item.get("product_name")
}
pantry_list = list(pantry_set)
prior = [p.strip() for p in prior_picks.split(",") if p.strip()]
profile_index = store.get_element_profiles(pantry_list + prior)
return get_role_candidates(
template_slug=template_id,
role_display=role,
pantry_set=pantry_set,
prior_picks=prior,
profile_index=profile_index,
)
finally:
store.close()
return await asyncio.to_thread(_get, session.db)
@router.post("/build", response_model=RecipeSuggestion)
async def build_recipe(
req: BuildRequest,
session: CloudUser = Depends(get_session),
) -> RecipeSuggestion:
"""Build a recipe from explicit role selections."""
def _build(db_path: Path) -> RecipeSuggestion | None:
store = Store(db_path)
try:
items = store.list_inventory(status="available")
pantry_set = {
item["product_name"]
for item in items
if item.get("product_name")
}
suggestion = build_from_selection(
template_slug=req.template_id,
role_overrides=req.role_overrides,
pantry_set=pantry_set,
)
if suggestion is None:
return None
# Persist to recipes table so the result can be saved/bookmarked.
# external_id encodes template + selections for stable dedup.
import hashlib as _hl, json as _js
sel_hash = _hl.md5(
_js.dumps(req.role_overrides, sort_keys=True).encode()
).hexdigest()[:8]
external_id = f"assembly:{req.template_id}:{sel_hash}"
real_id = store.upsert_built_recipe(
external_id=external_id,
title=suggestion.title,
ingredients=suggestion.matched_ingredients,
directions=suggestion.directions,
)
return suggestion.model_copy(update={"id": real_id})
finally:
store.close()
result = await asyncio.to_thread(_build, session.db)
if result is None:
raise HTTPException(
status_code=404,
detail="Template not found or required ingredient missing.",
)
return result
@router.get("/{recipe_id}")
async def get_recipe(recipe_id: int, session: CloudUser = Depends(get_session)) -> dict:
def _get(db_path: Path, rid: int) -> dict | None:
@ -554,57 +155,4 @@ async def get_recipe(recipe_id: int, session: CloudUser = Depends(get_session))
recipe = await asyncio.to_thread(_get, session.db, recipe_id)
if not recipe:
raise HTTPException(status_code=404, detail="Recipe not found.")
# Normalize corpus record into RecipeSuggestion shape so RecipeDetailPanel
# can render it without knowing it came from a direct DB lookup.
ingredient_names = recipe.get("ingredient_names") or []
if isinstance(ingredient_names, str):
import json as _json
try:
ingredient_names = _json.loads(ingredient_names)
except Exception:
ingredient_names = []
_directions_for_te = recipe.get("directions") or []
if isinstance(_directions_for_te, str):
import json as _json2
try:
_directions_for_te = _json2.loads(_directions_for_te)
except Exception:
_directions_for_te = []
if _directions_for_te:
_te = parse_time_effort(_directions_for_te)
_time_effort_out: dict | None = {
"active_min": _te.active_min,
"passive_min": _te.passive_min,
"total_min": _te.total_min,
"effort_label": _te.effort_label,
"equipment": _te.equipment,
"step_analyses": [
{"is_passive": sa.is_passive, "detected_minutes": sa.detected_minutes}
for sa in _te.step_analyses
],
}
else:
_time_effort_out = None
return {
"id": recipe.get("id"),
"title": recipe.get("title", ""),
"match_count": 0,
"matched_ingredients": ingredient_names,
"missing_ingredients": [],
"directions": recipe.get("directions") or [],
"prep_notes": [],
"swap_candidates": [],
"element_coverage": {},
"notes": recipe.get("notes") or "",
"level": 1,
"is_wildcard": False,
"nutrition": None,
"source_url": recipe.get("source_url") or None,
"complexity": None,
"estimated_time_min": None,
"time_effort": _time_effort_out,
}
return recipe

View file

@ -104,8 +104,6 @@ async def list_saved_recipes(
async def list_collections(
session: CloudUser = Depends(get_session),
) -> list[CollectionSummary]:
if not can_use("recipe_collections", session.tier):
raise HTTPException(status_code=403, detail="Collections require Paid tier.")
rows = await asyncio.to_thread(
_in_thread, session.db, lambda s: s.get_collections()
)

View file

@ -1,37 +0,0 @@
"""Session bootstrap endpoint — called once per app load by the frontend.
Logs auth= + tier= for log-based analytics without client-side tracking.
See Circuit-Forge/kiwi#86.
"""
from __future__ import annotations
import logging
from fastapi import APIRouter, Depends
from app.cloud_session import CloudUser, _auth_label, get_session
from app.core.config import settings
router = APIRouter()
log = logging.getLogger(__name__)
@router.get("/bootstrap")
def session_bootstrap(session: CloudUser = Depends(get_session)) -> dict:
"""Record auth type and tier for log-based analytics.
Expected log output:
INFO:app.api.endpoints.session: session auth=authed tier=paid
INFO:app.api.endpoints.session: session auth=anon tier=free
E2E test sessions (E2E_TEST_USER_ID) are logged at DEBUG so they don't
pollute analytics counts while still being visible when DEBUG=true.
"""
is_test = bool(settings.E2E_TEST_USER_ID and session.user_id == settings.E2E_TEST_USER_ID)
logger = log.debug if is_test else log.info
logger("session auth=%s tier=%s%s", _auth_label(session.user_id), session.tier, " e2e=true" if is_test else "")
return {
"auth": _auth_label(session.user_id),
"tier": session.tier,
"has_byok": session.has_byok,
}

View file

@ -10,7 +10,7 @@ from app.db.store import Store
router = APIRouter()
_ALLOWED_KEYS = frozenset({"cooking_equipment", "unit_system", "shopping_locale", "sensory_preferences", "time_first_layout"})
_ALLOWED_KEYS = frozenset({"cooking_equipment"})
class SettingBody(BaseModel):

View file

@ -1,233 +0,0 @@
"""Shopping list endpoints.
Free tier for all users (anonymous guests included shopping list is the
primary affiliate revenue surface). Confirm-purchase action is also Free:
it moves a checked item into pantry inventory without a tier gate so the
flow works for anyone who signs up or browses without an account.
Routes:
GET /shopping list items (with affiliate links)
POST /shopping add item manually
PATCH /shopping/{id} update (check/uncheck, rename, qty)
DELETE /shopping/{id} remove single item
DELETE /shopping/checked clear all checked items
DELETE /shopping/all clear entire list
POST /shopping/from-recipe bulk add gaps from a recipe
POST /shopping/{id}/confirm confirm purchase add to pantry inventory
"""
from __future__ import annotations
import asyncio
import logging
from fastapi import APIRouter, Depends, HTTPException, status
from app.cloud_session import CloudUser, get_session
from app.db.session import get_store
from app.db.store import Store
from app.models.schemas.shopping import (
BulkAddFromRecipeRequest,
ConfirmPurchaseRequest,
ShoppingItemCreate,
ShoppingItemResponse,
ShoppingItemUpdate,
)
from app.services.recipe.grocery_links import GroceryLinkBuilder
log = logging.getLogger(__name__)
router = APIRouter()
def _enrich(item: dict, builder: GroceryLinkBuilder) -> ShoppingItemResponse:
"""Attach live affiliate links to a raw store row."""
links = builder.build_links(item["name"])
return ShoppingItemResponse(
**{**item, "checked": bool(item.get("checked", 0))},
grocery_links=[{"ingredient": l.ingredient, "retailer": l.retailer, "url": l.url} for l in links],
)
def _in_thread(db_path, fn):
store = Store(db_path)
try:
return fn(store)
finally:
store.close()
# ── List ──────────────────────────────────────────────────────────────────────
def _locale_from_store(store: Store) -> str:
return store.get_setting("shopping_locale") or "us"
@router.get("", response_model=list[ShoppingItemResponse])
async def list_shopping_items(
include_checked: bool = True,
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
):
locale = await asyncio.to_thread(_in_thread, session.db, _locale_from_store)
builder = GroceryLinkBuilder(tier=session.tier, has_byok=session.has_byok, locale=locale)
items = await asyncio.to_thread(
_in_thread, session.db, lambda s: s.list_shopping_items(include_checked)
)
return [_enrich(i, builder) for i in items]
# ── Add manually ──────────────────────────────────────────────────────────────
@router.post("", response_model=ShoppingItemResponse, status_code=status.HTTP_201_CREATED)
async def add_shopping_item(
body: ShoppingItemCreate,
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
):
builder = GroceryLinkBuilder(tier=session.tier, has_byok=session.has_byok, locale=_locale_from_store(store))
item = await asyncio.to_thread(
_in_thread,
session.db,
lambda s: s.add_shopping_item(
name=body.name,
quantity=body.quantity,
unit=body.unit,
category=body.category,
notes=body.notes,
source=body.source,
recipe_id=body.recipe_id,
sort_order=body.sort_order,
),
)
return _enrich(item, builder)
# ── Bulk add from recipe ───────────────────────────────────────────────────────
@router.post("/from-recipe", response_model=list[ShoppingItemResponse], status_code=status.HTTP_201_CREATED)
async def add_from_recipe(
body: BulkAddFromRecipeRequest,
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
):
"""Add missing ingredients from a recipe to the shopping list.
Runs pantry gap analysis and adds only the items the user doesn't have
(unless include_covered=True). Skips duplicates already on the list.
"""
from app.services.meal_plan.shopping_list import compute_shopping_list
def _run(store: Store):
recipe = store.get_recipe(body.recipe_id)
if not recipe:
raise HTTPException(status_code=404, detail="Recipe not found")
inventory = store.list_inventory()
gaps, covered = compute_shopping_list([recipe], inventory)
targets = (gaps + covered) if body.include_covered else gaps
# Avoid duplicates already on the list
existing = {i["name"].lower() for i in store.list_shopping_items()}
added = []
for gap in targets:
if gap.ingredient_name.lower() in existing:
continue
item = store.add_shopping_item(
name=gap.ingredient_name,
quantity=None,
unit=gap.have_unit,
source="recipe",
recipe_id=body.recipe_id,
)
added.append(item)
return added
builder = GroceryLinkBuilder(tier=session.tier, has_byok=session.has_byok, locale=_locale_from_store(store))
items = await asyncio.to_thread(_in_thread, session.db, _run)
return [_enrich(i, builder) for i in items]
# ── Update ────────────────────────────────────────────────────────────────────
@router.patch("/{item_id}", response_model=ShoppingItemResponse)
async def update_shopping_item(
item_id: int,
body: ShoppingItemUpdate,
session: CloudUser = Depends(get_session),
store: Store = Depends(get_store),
):
builder = GroceryLinkBuilder(tier=session.tier, has_byok=session.has_byok, locale=_locale_from_store(store))
item = await asyncio.to_thread(
_in_thread,
session.db,
lambda s: s.update_shopping_item(item_id, **body.model_dump(exclude_none=True)),
)
if not item:
raise HTTPException(status_code=404, detail="Shopping item not found")
return _enrich(item, builder)
# ── Confirm purchase → pantry ─────────────────────────────────────────────────
@router.post("/{item_id}/confirm", status_code=status.HTTP_201_CREATED)
async def confirm_purchase(
item_id: int,
body: ConfirmPurchaseRequest,
session: CloudUser = Depends(get_session),
):
"""Confirm a checked item was purchased and add it to pantry inventory.
Human approval step: the user explicitly confirms what they actually bought
before it lands in their pantry. Returns the new inventory item.
"""
def _run(store: Store):
shopping_item = store.get_shopping_item(item_id)
if not shopping_item:
raise HTTPException(status_code=404, detail="Shopping item not found")
qty = body.quantity if body.quantity is not None else (shopping_item.get("quantity") or 1.0)
unit = body.unit or shopping_item.get("unit") or "count"
category = shopping_item.get("category")
product = store.get_or_create_product(
name=shopping_item["name"],
category=category,
)
inv_item = store.add_inventory_item(
product_id=product["id"],
location=body.location,
quantity=qty,
unit=unit,
source="manual",
)
# Mark the shopping item checked and leave it for the user to clear
store.update_shopping_item(item_id, checked=True)
return inv_item
return await asyncio.to_thread(_in_thread, session.db, _run)
# ── Delete ────────────────────────────────────────────────────────────────────
@router.delete("/{item_id}", status_code=status.HTTP_204_NO_CONTENT)
async def delete_shopping_item(
item_id: int,
session: CloudUser = Depends(get_session),
):
deleted = await asyncio.to_thread(
_in_thread, session.db, lambda s: s.delete_shopping_item(item_id)
)
if not deleted:
raise HTTPException(status_code=404, detail="Shopping item not found")
@router.delete("/checked", status_code=status.HTTP_204_NO_CONTENT)
async def clear_checked(session: CloudUser = Depends(get_session)):
await asyncio.to_thread(
_in_thread, session.db, lambda s: s.clear_checked_shopping_items()
)
@router.delete("/all", status_code=status.HTTP_204_NO_CONTENT)
async def clear_all(session: CloudUser = Depends(get_session)):
await asyncio.to_thread(
_in_thread, session.db, lambda s: s.clear_all_shopping_items()
)

View file

@ -1,26 +1,19 @@
from fastapi import APIRouter
from app.api.endpoints import health, receipts, export, inventory, ocr, recipes, settings, staples, feedback, feedback_attach, household, saved_recipes, imitate, meal_plans, orch_usage, session, shopping
from app.api.endpoints import health, receipts, export, inventory, ocr, recipes, settings, staples, feedback, household, saved_recipes, meal_plans
from app.api.endpoints.community import router as community_router
from app.api.endpoints.recipe_tags import router as recipe_tags_router
api_router = APIRouter()
api_router.include_router(session.router, prefix="/session", tags=["session"])
api_router.include_router(health.router, prefix="/health", tags=["health"])
api_router.include_router(receipts.router, prefix="/receipts", tags=["receipts"])
api_router.include_router(ocr.router, prefix="/receipts", tags=["ocr"])
api_router.include_router(export.router, tags=["export"])
api_router.include_router(inventory.router, prefix="/inventory", tags=["inventory"])
api_router.include_router(saved_recipes.router, prefix="/recipes/saved", tags=["saved-recipes"])
api_router.include_router(recipes.router, prefix="/recipes", tags=["recipes"])
api_router.include_router(settings.router, prefix="/settings", tags=["settings"])
api_router.include_router(staples.router, prefix="/staples", tags=["staples"])
api_router.include_router(feedback.router, prefix="/feedback", tags=["feedback"])
api_router.include_router(feedback_attach.router, prefix="/feedback", tags=["feedback"])
api_router.include_router(household.router, prefix="/household", tags=["household"])
api_router.include_router(imitate.router, prefix="/imitate", tags=["imitate"])
api_router.include_router(meal_plans.router, prefix="/meal-plans", tags=["meal-plans"])
api_router.include_router(orch_usage.router, prefix="/orch-usage", tags=["orch-usage"])
api_router.include_router(shopping.router, prefix="/shopping", tags=["shopping"])
api_router.include_router(community_router)
api_router.include_router(recipe_tags_router)
api_router.include_router(health.router, prefix="/health", tags=["health"])
api_router.include_router(receipts.router, prefix="/receipts", tags=["receipts"])
api_router.include_router(ocr.router, prefix="/receipts", tags=["ocr"])
api_router.include_router(export.router, tags=["export"])
api_router.include_router(inventory.router, prefix="/inventory", tags=["inventory"])
api_router.include_router(recipes.router, prefix="/recipes", tags=["recipes"])
api_router.include_router(settings.router, prefix="/settings", tags=["settings"])
api_router.include_router(staples.router, prefix="/staples", tags=["staples"])
api_router.include_router(feedback.router, prefix="/feedback", tags=["feedback"])
api_router.include_router(household.router, prefix="/household", tags=["household"])
api_router.include_router(saved_recipes.router, prefix="/recipes/saved", tags=["saved-recipes"])
api_router.include_router(meal_plans.router, prefix="/meal-plans", tags=["meal-plans"])
api_router.include_router(community_router)

View file

@ -22,12 +22,10 @@ import time
from dataclasses import dataclass
from pathlib import Path
import uuid
import jwt as pyjwt
import requests
import yaml
from fastapi import Depends, HTTPException, Request, Response
from fastapi import Depends, HTTPException, Request
log = logging.getLogger(__name__)
@ -84,15 +82,6 @@ _TIER_CACHE_TTL = 300 # 5 minutes
TIERS = ["free", "paid", "premium", "ultra"]
def _auth_label(user_id: str) -> str:
"""Classify a user_id into a short tag for structured log lines. No PII emitted."""
if user_id in ("local", "local-dev"):
return "local"
if user_id.startswith("anon-"):
return "anon"
return "authed"
# ── Domain ────────────────────────────────────────────────────────────────────
@dataclass(frozen=True)
@ -103,7 +92,6 @@ class CloudUser:
has_byok: bool # True if a configured LLM backend is present in llm.yaml
household_id: str | None = None
is_household_owner: bool = False
license_key: str | None = None # key_display for lifetime/founders keys; None for subscription/free
# ── JWT validation ─────────────────────────────────────────────────────────────
@ -144,16 +132,16 @@ def _ensure_provisioned(user_id: str) -> None:
log.warning("Heimdall provision failed for user %s: %s", user_id, exc)
def _fetch_cloud_tier(user_id: str) -> tuple[str, str | None, bool, str | None]:
"""Returns (tier, household_id | None, is_household_owner, license_key | None)."""
def _fetch_cloud_tier(user_id: str) -> tuple[str, str | None, bool]:
"""Returns (tier, household_id | None, is_household_owner)."""
now = time.monotonic()
cached = _TIER_CACHE.get(user_id)
if cached and (now - cached[1]) < _TIER_CACHE_TTL:
entry = cached[0]
return entry["tier"], entry.get("household_id"), entry.get("is_household_owner", False), entry.get("license_key")
return entry["tier"], entry.get("household_id"), entry.get("is_household_owner", False)
if not HEIMDALL_ADMIN_TOKEN:
return "free", None, False, None
return "free", None, False
try:
resp = requests.post(
f"{HEIMDALL_URL}/admin/cloud/resolve",
@ -165,13 +153,12 @@ def _fetch_cloud_tier(user_id: str) -> tuple[str, str | None, bool, str | None]:
tier = data.get("tier", "free")
household_id = data.get("household_id")
is_owner = data.get("is_household_owner", False)
license_key = data.get("key_display")
except Exception as exc:
log.warning("Heimdall tier resolve failed for user %s: %s", user_id, exc)
tier, household_id, is_owner, license_key = "free", None, False, None
tier, household_id, is_owner = "free", None, False
_TIER_CACHE[user_id] = ({"tier": tier, "household_id": household_id, "is_household_owner": is_owner, "license_key": license_key}, now)
return tier, household_id, is_owner, license_key
_TIER_CACHE[user_id] = ({"tier": tier, "household_id": household_id, "is_household_owner": is_owner}, now)
return tier, household_id, is_owner
def _user_db_path(user_id: str, household_id: str | None = None) -> Path:
@ -183,17 +170,6 @@ def _user_db_path(user_id: str, household_id: str | None = None) -> Path:
return path
def _anon_guest_db_path(guest_id: str) -> Path:
"""Per-session DB for unauthenticated guest visitors.
Each anonymous visitor gets an isolated SQLite DB keyed by their guest UUID
cookie, so shopping lists and affiliate interactions never bleed across sessions.
"""
path = CLOUD_DATA_ROOT / f"anon-{guest_id}" / "kiwi.db"
path.parent.mkdir(parents=True, exist_ok=True)
return path
# ── BYOK detection ────────────────────────────────────────────────────────────
_LLM_CONFIG_PATH = Path.home() / ".config" / "circuitforge" / "llm.yaml"
@ -219,52 +195,20 @@ def _detect_byok(config_path: Path = _LLM_CONFIG_PATH) -> bool:
# ── FastAPI dependency ────────────────────────────────────────────────────────
_GUEST_COOKIE = "kiwi_guest_id"
_GUEST_COOKIE_MAX_AGE = 60 * 60 * 24 * 90 # 90 days
def _resolve_guest_session(request: Request, response: Response, has_byok: bool) -> CloudUser:
"""Return a per-session anonymous CloudUser, creating a guest UUID cookie if needed."""
guest_id = request.cookies.get(_GUEST_COOKIE, "").strip()
is_new = not guest_id
if is_new:
guest_id = str(uuid.uuid4())
log.debug("New guest session assigned: anon-%s", guest_id[:8])
# Secure flag only when the request actually arrived over HTTPS
# (Caddy sets X-Forwarded-Proto=https in cloud; absent on direct port access).
# Avoids losing the session cookie on HTTP direct-port testing of the cloud stack.
is_https = request.headers.get("x-forwarded-proto", "http").lower() == "https"
response.set_cookie(
key=_GUEST_COOKIE,
value=guest_id,
max_age=_GUEST_COOKIE_MAX_AGE,
httponly=True,
samesite="lax",
secure=is_https,
)
return CloudUser(
user_id=f"anon-{guest_id}",
tier="free",
db=_anon_guest_db_path(guest_id),
has_byok=has_byok,
)
def get_session(request: Request, response: Response) -> CloudUser:
def get_session(request: Request) -> CloudUser:
"""FastAPI dependency — resolves the current user from the request.
Local mode: fully-privileged "local" user pointing at local DB.
Cloud mode: validates X-CF-Session JWT, provisions license, resolves tier.
Dev bypass: if CLOUD_AUTH_BYPASS_IPS is set and the client IP matches,
returns a "local" session without JWT validation (dev/LAN use only).
Anonymous: per-session UUID cookie isolates each guest visitor's data.
"""
has_byok = _detect_byok()
if not CLOUD_MODE:
return CloudUser(user_id="local", tier="local", db=_LOCAL_KIWI_DB, has_byok=has_byok)
# Prefer X-Real-IP (set by Caddy from the actual client address) over the
# Prefer X-Real-IP (set by nginx from the actual client address) over the
# TCP peer address (which is nginx's container IP when behind the proxy).
client_ip = (
request.headers.get("x-real-ip", "")
@ -276,23 +220,20 @@ def get_session(request: Request, response: Response) -> CloudUser:
dev_db = _user_db_path("local-dev")
return CloudUser(user_id="local-dev", tier="local", db=dev_db, has_byok=has_byok)
# Resolve cf_session JWT: prefer the explicit header injected by Caddy, then
# fall back to the cf_session cookie value. Other cookies (e.g. kiwi_guest_id)
# must never be treated as auth tokens.
raw_session = request.headers.get("x-cf-session", "").strip()
if not raw_session:
raw_session = request.cookies.get("cf_session", "").strip()
raw_header = (
request.headers.get("x-cf-session", "")
or request.headers.get("cookie", "")
)
if not raw_header:
raise HTTPException(status_code=401, detail="Not authenticated")
if not raw_session:
return _resolve_guest_session(request, response, has_byok)
token = _extract_session_token(raw_session) # gitleaks:allow — function name, not a secret
token = _extract_session_token(raw_header) # gitleaks:allow — function name, not a secret
if not token:
return _resolve_guest_session(request, response, has_byok)
raise HTTPException(status_code=401, detail="Not authenticated")
user_id = validate_session_jwt(token)
_ensure_provisioned(user_id)
tier, household_id, is_household_owner, license_key = _fetch_cloud_tier(user_id)
tier, household_id, is_household_owner = _fetch_cloud_tier(user_id)
return CloudUser(
user_id=user_id,
tier=tier,
@ -300,7 +241,6 @@ def get_session(request: Request, response: Response) -> CloudUser:
has_byok=has_byok,
household_id=household_id,
is_household_owner=is_household_owner,
license_key=license_key,
)

View file

@ -35,24 +35,6 @@ class Settings:
# Database
DB_PATH: Path = Path(os.environ.get("DB_PATH", str(DATA_DIR / "kiwi.db")))
# Pre-computed browse counts cache (small SQLite, separate from corpus).
# Written by the nightly refresh task and by infer_recipe_tags.py.
# Set BROWSE_COUNTS_PATH to a bind-mounted path if you want the host
# pipeline to share counts with the container without re-running FTS.
BROWSE_COUNTS_PATH: Path = Path(
os.environ.get("BROWSE_COUNTS_PATH", str(DATA_DIR / "browse_counts.db"))
)
# Community feature settings
COMMUNITY_DB_URL: str | None = os.environ.get("COMMUNITY_DB_URL") or None
COMMUNITY_PSEUDONYM_SALT: str = os.environ.get(
"COMMUNITY_PSEUDONYM_SALT", "kiwi-default-salt-change-in-prod"
)
COMMUNITY_CLOUD_FEED_URL: str = os.environ.get(
"COMMUNITY_CLOUD_FEED_URL",
"https://menagerie.circuitforge.tech/kiwi/api/v1/community/posts",
)
# Processing
MAX_CONCURRENT_JOBS: int = int(os.environ.get("MAX_CONCURRENT_JOBS", "4"))
USE_GPU: bool = os.environ.get("USE_GPU", "true").lower() in ("1", "true", "yes")
@ -68,18 +50,18 @@ class Settings:
# CFOrchClient reads CF_LICENSE_KEY automatically; exposed here for startup validation.
CF_LICENSE_KEY: str | None = os.environ.get("CF_LICENSE_KEY")
# E2E test account — analytics logging is suppressed for this user_id so test
# runs don't pollute session counts. Set to the Directus UUID of the test user.
E2E_TEST_USER_ID: str | None = os.environ.get("E2E_TEST_USER_ID") or None
# Feature flags
ENABLE_OCR: bool = os.environ.get("ENABLE_OCR", "false").lower() in ("1", "true", "yes")
# Use OrchestratedScheduler (coordinator-aware, multi-GPU fan-out) instead of
# LocalScheduler. Defaults to true in CLOUD_MODE; can be set independently
# for multi-GPU local rigs that don't need full cloud auth.
USE_ORCH_SCHEDULER: bool | None = (
None if os.environ.get("USE_ORCH_SCHEDULER") is None
else os.environ.get("USE_ORCH_SCHEDULER", "").lower() in ("1", "true", "yes")
# Community feature
# COMMUNITY_DB_URL: unset = community writes disabled (local/offline mode, fail soft)
COMMUNITY_DB_URL: str | None = os.environ.get("COMMUNITY_DB_URL") or None
COMMUNITY_PSEUDONYM_SALT: str = os.environ.get(
"COMMUNITY_PSEUDONYM_SALT", "kiwi-default-salt-change-in-prod"
)
COMMUNITY_CLOUD_FEED_URL: str = os.environ.get(
"COMMUNITY_CLOUD_FEED_URL",
"https://menagerie.circuitforge.tech/kiwi/api/v1/community/posts",
)
# Runtime

View file

@ -1,5 +0,0 @@
-- Migration 022: Add is_generic flag to recipes
-- Generic recipes are catch-all/dump recipes with loose ingredient lists
-- that should not appear in Level 1 (deterministic "use what I have") results.
-- Admins can mark recipes via the recipe editor or a bulk backfill script.
ALTER TABLE recipes ADD COLUMN is_generic INTEGER NOT NULL DEFAULT 0;

View file

@ -1,4 +1,4 @@
-- 028_community_pseudonyms.sql
-- 026_community_pseudonyms.sql
-- Per-user pseudonym store: maps the user's chosen community display name
-- to their Directus user ID. This table lives in per-user kiwi.db only.
-- It is NEVER replicated to the community PostgreSQL — pseudonym isolation is by design.

View file

@ -1,49 +0,0 @@
-- Migration 029: Add inferred_tags column and update FTS index to include it.
--
-- inferred_tags holds a JSON array of normalized tag strings derived by
-- scripts/pipeline/infer_recipe_tags.py (e.g. ["cuisine:Italian",
-- "dietary:Low-Carb", "flavor:Umami", "can_be:Gluten-Free"]).
--
-- The FTS5 browser table is rebuilt to index inferred_tags alongside
-- category and keywords so browse domain queries match against all signals.
-- 1. Add inferred_tags column (empty array default; populated by pipeline run)
ALTER TABLE recipes ADD COLUMN inferred_tags TEXT NOT NULL DEFAULT '[]';
-- 2. Drop old FTS table and triggers that only covered category + keywords
DROP TRIGGER IF EXISTS recipes_ai;
DROP TRIGGER IF EXISTS recipes_ad;
DROP TRIGGER IF EXISTS recipes_au;
DROP TABLE IF EXISTS recipe_browser_fts;
-- 3. Recreate FTS5 table: now indexes category, keywords, AND inferred_tags
CREATE VIRTUAL TABLE recipe_browser_fts USING fts5(
category,
keywords,
inferred_tags,
content=recipes,
content_rowid=id
);
-- 4. Triggers to keep FTS in sync with recipes table changes
CREATE TRIGGER recipes_ai AFTER INSERT ON recipes BEGIN
INSERT INTO recipe_browser_fts(rowid, category, keywords, inferred_tags)
VALUES (new.id, new.category, new.keywords, new.inferred_tags);
END;
CREATE TRIGGER recipes_ad AFTER DELETE ON recipes BEGIN
INSERT INTO recipe_browser_fts(recipe_browser_fts, rowid, category, keywords, inferred_tags)
VALUES ('delete', old.id, old.category, old.keywords, old.inferred_tags);
END;
CREATE TRIGGER recipes_au AFTER UPDATE ON recipes BEGIN
INSERT INTO recipe_browser_fts(recipe_browser_fts, rowid, category, keywords, inferred_tags)
VALUES ('delete', old.id, old.category, old.keywords, old.inferred_tags);
INSERT INTO recipe_browser_fts(rowid, category, keywords, inferred_tags)
VALUES (new.id, new.category, new.keywords, new.inferred_tags);
END;
-- 5. Populate FTS from current table state
-- (inferred_tags is '[]' for all rows at this point; run infer_recipe_tags.py
-- to populate, then the FTS will be rebuilt as part of that script.)
INSERT INTO recipe_browser_fts(recipe_browser_fts) VALUES('rebuild');

View file

@ -1,5 +0,0 @@
-- Migration 030: open-package tracking
-- Adds opened_date to track when a multi-use item was first opened,
-- enabling secondary shelf-life windows (e.g. salsa: 1 year sealed → 2 weeks opened).
ALTER TABLE inventory_items ADD COLUMN opened_date TEXT;

View file

@ -1,4 +0,0 @@
-- Migration 031: add disposal_reason for waste logging (#60)
-- status='discarded' already exists in the CHECK constraint from migration 002.
-- This column stores free-text reason (optional) and calm-framing presets.
ALTER TABLE inventory_items ADD COLUMN disposal_reason TEXT;

View file

@ -1,4 +0,0 @@
-- 032_meal_plan_unique_week.sql
-- Prevent duplicate plans for the same week.
-- Existing duplicates must be resolved before applying (keep MIN(id) per week_start).
CREATE UNIQUE INDEX IF NOT EXISTS idx_meal_plans_week_start ON meal_plans (week_start);

View file

@ -1,21 +0,0 @@
-- Migration 033: standalone shopping list
-- Items can be added manually, from recipe gap analysis, or from the recipe browser.
-- Affiliate links are computed at query time by the API layer (never stored).
CREATE TABLE IF NOT EXISTS shopping_list_items (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
quantity REAL,
unit TEXT,
category TEXT,
checked INTEGER NOT NULL DEFAULT 0, -- 0=want, 1=in-cart/checked off
notes TEXT,
source TEXT NOT NULL DEFAULT 'manual', -- manual | recipe | meal_plan
recipe_id INTEGER REFERENCES recipes(id) ON DELETE SET NULL,
sort_order INTEGER NOT NULL DEFAULT 0,
created_at TEXT NOT NULL DEFAULT (datetime('now')),
updated_at TEXT NOT NULL DEFAULT (datetime('now'))
);
CREATE INDEX IF NOT EXISTS idx_shopping_list_checked
ON shopping_list_items (checked, sort_order);

View file

@ -1,14 +0,0 @@
-- Migration 034: async recipe generation job queue
CREATE TABLE IF NOT EXISTS recipe_jobs (
id INTEGER PRIMARY KEY AUTOINCREMENT,
job_id TEXT NOT NULL UNIQUE,
user_id TEXT NOT NULL,
status TEXT NOT NULL DEFAULT 'queued',
request TEXT NOT NULL,
result TEXT,
error TEXT,
created_at TEXT NOT NULL DEFAULT (datetime('now')),
updated_at TEXT NOT NULL DEFAULT (datetime('now'))
);
CREATE INDEX IF NOT EXISTS idx_recipe_jobs_job_id ON recipe_jobs (job_id);
CREATE INDEX IF NOT EXISTS idx_recipe_jobs_user_id ON recipe_jobs (user_id, created_at DESC);

View file

@ -1,12 +0,0 @@
-- Migration 035: add sensory_tags column for sensory profile filtering
--
-- sensory_tags holds a JSON object with texture, smell, and noise signals:
-- {"textures": ["mushy", "creamy"], "smell": "pungent", "noise": "moderate"}
--
-- Empty object '{}' means untagged — these recipes pass ALL sensory filters
-- (graceful degradation when tag_sensory_profiles.py has not yet been run).
--
-- Populated offline by: python scripts/tag_sensory_profiles.py [path/to/kiwi.db]
-- No FTS rebuild needed — sensory_tags is filtered in Python after candidate fetch.
ALTER TABLE recipes ADD COLUMN sensory_tags TEXT NOT NULL DEFAULT '{}';

View file

@ -1,26 +0,0 @@
-- Migration 036: captured_products local cache
-- Products captured via visual label scanning (kiwi#79).
-- Keyed by barcode; checked before FDC/OFF on future scans so each product
-- is only captured once per device.
CREATE TABLE IF NOT EXISTS captured_products (
id INTEGER PRIMARY KEY AUTOINCREMENT,
barcode TEXT UNIQUE NOT NULL,
product_name TEXT,
brand TEXT,
serving_size_g REAL,
calories REAL,
fat_g REAL,
saturated_fat_g REAL,
carbs_g REAL,
sugar_g REAL,
fiber_g REAL,
protein_g REAL,
sodium_mg REAL,
ingredient_names TEXT NOT NULL DEFAULT '[]', -- JSON array
allergens TEXT NOT NULL DEFAULT '[]', -- JSON array
confidence REAL,
source TEXT NOT NULL DEFAULT 'visual_capture',
captured_at TEXT NOT NULL DEFAULT (datetime('now')),
confirmed_by_user INTEGER NOT NULL DEFAULT 0
);

View file

@ -11,7 +11,6 @@ from typing import Any
from circuitforge_core.db.base import get_connection
from circuitforge_core.db.migrations import run_migrations
from app.services.recipe.sensory import SensoryExclude, passes_sensory_filter
MIGRATIONS_DIR = Path(__file__).parent / "migrations"
@ -24,25 +23,12 @@ _COUNT_CACHE: dict[tuple[str, ...], int] = {}
class Store:
def __init__(self, db_path: Path, key: str = "") -> None:
import os
self._db_path = str(db_path)
self.conn: sqlite3.Connection = get_connection(db_path, key)
self.conn.execute("PRAGMA journal_mode=WAL")
self.conn.execute("PRAGMA foreign_keys=ON")
run_migrations(self.conn, MIGRATIONS_DIR)
# When RECIPE_DB_PATH is set (cloud mode), attach the shared read-only
# corpus DB as the "corpus" schema so per-user DBs can access recipe data.
# _cp (corpus prefix) is "corpus." in cloud mode, "" in local mode.
corpus_path = os.environ.get("RECIPE_DB_PATH", "")
if corpus_path:
self.conn.execute("ATTACH DATABASE ? AS corpus", (corpus_path,))
self._cp = "corpus."
self._corpus_path = corpus_path
else:
self._cp = ""
self._corpus_path = self._db_path
def close(self) -> None:
self.conn.close()
@ -60,9 +46,7 @@ class Store:
# saved recipe columns
"style_tags",
# meal plan columns
"meal_types",
# captured_products columns
"allergens"):
"meal_types"):
if key in d and isinstance(d[key], str):
try:
d[key] = json.loads(d[key])
@ -234,8 +218,7 @@ class Store:
def update_inventory_item(self, item_id: int, **kwargs) -> dict[str, Any] | None:
allowed = {"quantity", "unit", "location", "sublocation",
"purchase_date", "expiration_date", "opened_date",
"status", "notes", "consumed_at", "disposal_reason"}
"expiration_date", "status", "notes", "consumed_at"}
updates = {k: v for k, v in kwargs.items() if k in allowed}
if not updates:
return self.get_inventory_item(item_id)
@ -248,32 +231,6 @@ class Store:
self.conn.commit()
return self.get_inventory_item(item_id)
def partial_consume_item(
self,
item_id: int,
consume_qty: float,
consumed_at: str,
) -> dict[str, Any] | None:
"""Decrement quantity by consume_qty. Mark consumed when quantity reaches 0."""
row = self.get_inventory_item(item_id)
if row is None:
return None
remaining = max(0.0, round(row["quantity"] - consume_qty, 6))
if remaining <= 0:
self.conn.execute(
"UPDATE inventory_items SET quantity = 0, status = 'consumed',"
" consumed_at = ?, updated_at = datetime('now') WHERE id = ?",
(consumed_at, item_id),
)
else:
self.conn.execute(
"UPDATE inventory_items SET quantity = ?, updated_at = datetime('now')"
" WHERE id = ?",
(remaining, item_id),
)
self.conn.commit()
return self.get_inventory_item(item_id)
def expiring_soon(self, days: int = 7) -> list[dict[str, Any]]:
return self._fetch_all(
"""SELECT i.*, p.name as product_name, p.category
@ -388,9 +345,8 @@ class Store:
def _fts_ready(self) -> bool:
"""Return True if the recipes_fts virtual table exists."""
schema = "corpus" if self._cp else "main"
row = self._fetch_one(
f"SELECT 1 FROM {schema}.sqlite_master WHERE type='table' AND name='recipes_fts'"
"SELECT 1 FROM sqlite_master WHERE type='table' AND name='recipes_fts'"
)
return row is not None
@ -617,7 +573,6 @@ class Store:
max_carbs_g: float | None = None,
max_sodium_mg: float | None = None,
excluded_ids: list[int] | None = None,
exclude_generic: bool = False,
) -> list[dict]:
"""Find recipes containing any of the given ingredient names.
Scores by match count and returns highest-scoring first.
@ -627,9 +582,6 @@ class Store:
Nutrition filters use NULL-passthrough: rows without nutrition data
always pass (they may be estimated or absent entirely).
exclude_generic: when True, skips recipes marked is_generic=1.
Pass True for Level 1 ("Use What I Have") to suppress catch-all recipes.
"""
if not ingredient_names:
return []
@ -655,8 +607,6 @@ class Store:
placeholders = ",".join("?" * len(excluded_ids))
extra_clauses.append(f"r.id NOT IN ({placeholders})")
extra_params.extend(excluded_ids)
if exclude_generic:
extra_clauses.append("r.is_generic = 0")
where_extra = (" AND " + " AND ".join(extra_clauses)) if extra_clauses else ""
if self._fts_ready():
@ -681,12 +631,10 @@ class Store:
return []
# Pull up to 10× limit candidates so ranking has enough headroom.
# FTS5 pseudo-column in WHERE uses bare table name, not schema-qualified.
c = self._cp
sql = f"""
SELECT r.*
FROM {c}recipes_fts
JOIN {c}recipes r ON r.id = {c}recipes_fts.rowid
FROM recipes_fts
JOIN recipes r ON r.id = recipes_fts.rowid
WHERE recipes_fts MATCH ?
{where_extra}
LIMIT ?
@ -720,10 +668,9 @@ class Store:
"CASE WHEN r.ingredient_names LIKE ? THEN 1 ELSE 0 END"
for _ in ingredient_names
)
c = self._cp
sql = f"""
SELECT r.*, ({match_score}) AS match_count
FROM {c}recipes r
FROM recipes r
WHERE ({like_clauses})
{where_extra}
ORDER BY match_count DESC, r.id ASC
@ -733,107 +680,7 @@ class Store:
return self._fetch_all(sql, tuple(all_params))
def get_recipe(self, recipe_id: int) -> dict | None:
row = self._fetch_one(f"SELECT * FROM {self._cp}recipes WHERE id = ?", (recipe_id,))
if row is None and self._cp:
# Fall back to user's own assembled recipes in main schema
row = self._fetch_one("SELECT * FROM recipes WHERE id = ?", (recipe_id,))
return row
# --- Async recipe jobs ---
def create_recipe_job(self, job_id: str, user_id: str, request_json: str) -> sqlite3.Row:
return self._insert_returning(
"INSERT INTO recipe_jobs (job_id, user_id, status, request) VALUES (?,?,?,?) RETURNING *",
(job_id, user_id, "queued", request_json),
)
def get_recipe_job(self, job_id: str, user_id: str) -> sqlite3.Row | None:
return self._fetch_one(
"SELECT * FROM recipe_jobs WHERE job_id=? AND user_id=?",
(job_id, user_id),
)
def update_recipe_job_running(self, job_id: str) -> None:
self.conn.execute(
"UPDATE recipe_jobs SET status='running', updated_at=datetime('now') WHERE job_id=?",
(job_id,),
)
self.conn.commit()
def complete_recipe_job(self, job_id: str, result_json: str) -> None:
self.conn.execute(
"UPDATE recipe_jobs SET status='done', result=?, updated_at=datetime('now') WHERE job_id=?",
(result_json, job_id),
)
self.conn.commit()
def fail_recipe_job(self, job_id: str, error: str) -> None:
self.conn.execute(
"UPDATE recipe_jobs SET status='failed', error=?, updated_at=datetime('now') WHERE job_id=?",
(error, job_id),
)
self.conn.commit()
def upsert_built_recipe(
self,
external_id: str,
title: str,
ingredients: list[str],
directions: list[str],
) -> int:
"""Persist an assembly-built recipe and return its DB id.
Uses external_id as a stable dedup key so the same build slug doesn't
accumulate duplicate rows across multiple user sessions.
"""
import json as _json
self.conn.execute(
"""
INSERT OR IGNORE INTO recipes
(external_id, title, ingredients, ingredient_names, directions, source)
VALUES (?, ?, ?, ?, ?, 'assembly')
""",
(
external_id,
title,
_json.dumps(ingredients),
_json.dumps(ingredients),
_json.dumps(directions),
),
)
# Update title in case the build was re-run with tweaked selections
self.conn.execute(
"UPDATE recipes SET title = ? WHERE external_id = ?",
(title, external_id),
)
self.conn.commit()
row = self._fetch_one(
"SELECT id FROM recipes WHERE external_id = ?", (external_id,)
)
return row["id"] # type: ignore[index]
def get_element_profiles(self, names: list[str]) -> dict[str, list[str]]:
"""Return {ingredient_name: [element_tag, ...]} for the given names.
Only names present in ingredient_profiles are returned -- missing names
are silently omitted so callers can distinguish "no profile" from "empty
elements list".
"""
if not names:
return {}
placeholders = ",".join("?" * len(names))
rows = self._fetch_all(
f"SELECT name, elements FROM {self._cp}ingredient_profiles WHERE name IN ({placeholders})",
tuple(names),
)
result: dict[str, list[str]] = {}
for row in rows:
try:
elements = json.loads(row["elements"]) if row["elements"] else []
except (json.JSONDecodeError, TypeError):
elements = []
result[row["name"]] = elements
return result
return self._fetch_one("SELECT * FROM recipes WHERE id = ?", (recipe_id,))
# ── rate limits ───────────────────────────────────────────────────────
@ -964,25 +811,12 @@ class Store:
"title": "r.title ASC",
}.get(sort_by, "sr.saved_at DESC")
c = self._cp
# In corpus-attached (cloud) mode: try corpus recipes first, fall back
# to user's own assembled recipes. In local mode: single join suffices.
if c:
recipe_join = (
f"LEFT JOIN {c}recipes rc ON rc.id = sr.recipe_id "
"LEFT JOIN recipes rm ON rm.id = sr.recipe_id"
)
title_col = "COALESCE(rc.title, rm.title) AS title"
else:
recipe_join = "JOIN recipes rc ON rc.id = sr.recipe_id"
title_col = "rc.title"
if collection_id is not None:
return self._fetch_all(
f"""
SELECT sr.*, {title_col}
SELECT sr.*, r.title
FROM saved_recipes sr
{recipe_join}
JOIN recipes r ON r.id = sr.recipe_id
JOIN recipe_collection_members rcm ON rcm.saved_recipe_id = sr.id
WHERE rcm.collection_id = ?
ORDER BY {order}
@ -991,9 +825,9 @@ class Store:
)
return self._fetch_all(
f"""
SELECT sr.*, {title_col}
SELECT sr.*, r.title
FROM saved_recipes sr
{recipe_join}
JOIN recipes r ON r.id = sr.recipe_id
ORDER BY {order}
""",
)
@ -1008,26 +842,10 @@ class Store:
# ── recipe collections ────────────────────────────────────────────────
def create_collection(self, name: str, description: str | None) -> dict:
# INSERT RETURNING * omits aggregate columns (e.g. member_count); re-query
# with the same SELECT used by get_collections() so the response shape is consistent.
cur = self.conn.execute(
"INSERT INTO recipe_collections (name, description) VALUES (?, ?)",
return self._insert_returning(
"INSERT INTO recipe_collections (name, description) VALUES (?, ?) RETURNING *",
(name, description),
)
self.conn.commit()
new_id = cur.lastrowid
row = self._fetch_one(
"""
SELECT rc.*,
COUNT(rcm.saved_recipe_id) AS member_count
FROM recipe_collections rc
LEFT JOIN recipe_collection_members rcm ON rcm.collection_id = rc.id
WHERE rc.id = ?
GROUP BY rc.id
""",
(new_id,),
)
return row # type: ignore[return-value]
def delete_collection(self, collection_id: int) -> None:
self.conn.execute(
@ -1089,38 +907,17 @@ class Store:
# ── recipe browser ────────────────────────────────────────────────────
def get_browser_categories(
self,
domain: str,
keywords_by_category: dict[str, list[str]],
has_subcategories_by_category: dict[str, bool] | None = None,
self, domain: str, keywords_by_category: dict[str, list[str]]
) -> list[dict]:
"""Return [{category, recipe_count, has_subcategories}] for each category.
"""Return [{category, recipe_count}] for each category in the domain.
keywords_by_category maps category name keyword list for counting.
has_subcategories_by_category maps category name bool (optional;
defaults to False for all categories when omitted).
keywords_by_category maps category name to the keyword list used to
match against recipes.category and recipes.keywords.
"""
results = []
for category, keywords in keywords_by_category.items():
count = self._count_recipes_for_keywords(keywords)
results.append({
"category": category,
"recipe_count": count,
"has_subcategories": (has_subcategories_by_category or {}).get(category, False),
})
return results
def get_browser_subcategories(
self, domain: str, keywords_by_subcategory: dict[str, list[str]]
) -> list[dict]:
"""Return [{subcategory, recipe_count}] for each subcategory.
Mirrors get_browser_categories but for the second level.
"""
results = []
for subcat, keywords in keywords_by_subcategory.items():
count = self._count_recipes_for_keywords(keywords)
results.append({"subcategory": subcat, "recipe_count": count})
results.append({"category": category, "recipe_count": count})
return results
@staticmethod
@ -1132,16 +929,12 @@ class Store:
def _count_recipes_for_keywords(self, keywords: list[str]) -> int:
if not keywords:
return 0
# Use corpus path as cache key so all cloud users share the same counts.
cache_key = (self._corpus_path, *sorted(keywords))
cache_key = (self._db_path, *sorted(keywords))
if cache_key in _COUNT_CACHE:
return _COUNT_CACHE[cache_key]
match_expr = self._browser_fts_query(keywords)
c = self._cp
# FTS5 pseudo-column in WHERE is always the bare (unqualified) table name,
# even when the table is accessed through an ATTACHed schema.
row = self.conn.execute(
f"SELECT count(*) FROM {c}recipe_browser_fts WHERE recipe_browser_fts MATCH ?",
"SELECT count(*) FROM recipe_browser_fts WHERE recipe_browser_fts MATCH ?",
(match_expr,),
).fetchone()
count = row[0] if row else 0
@ -1150,263 +943,61 @@ class Store:
def browse_recipes(
self,
keywords: list[str] | None,
keywords: list[str],
page: int,
page_size: int,
pantry_items: list[str] | None = None,
q: str | None = None,
sort: str = "default",
sensory_exclude: SensoryExclude | None = None,
) -> dict:
"""Return a page of recipes matching the keyword set.
Pass keywords=None to browse all recipes without category filtering.
Each recipe row includes match_pct (float | None) when pantry_items
is provided. match_pct is the fraction of ingredient_names covered by
the pantry set computed deterministically, no LLM needed.
q: optional title substring filter (case-insensitive LIKE).
sort: "default" (corpus order) | "alpha" (AZ) | "alpha_desc" (ZA)
| "match" (pantry coverage DESC falls back to default when no pantry).
"""
if keywords is not None and not keywords:
if not keywords:
return {"recipes": [], "total": 0, "page": page}
match_expr = self._browser_fts_query(keywords)
offset = (page - 1) * page_size
c = self._cp
pantry_set = {p.lower() for p in pantry_items} if pantry_items else None
# "match" sort requires pantry items; fall back gracefully when absent.
effective_sort = sort if (sort != "match" or pantry_set) else "default"
# Reuse cached count — avoids a second index scan on every page turn.
total = self._count_recipes_for_keywords(keywords)
order_clause = {
"alpha": "ORDER BY title ASC",
"alpha_desc": "ORDER BY title DESC",
}.get(effective_sort, "ORDER BY id ASC")
q_param = f"%{q.strip()}%" if q and q.strip() else None
# ── match sort: push match_pct computation into SQL so ORDER BY works ──
if effective_sort == "match" and pantry_set:
return self._browse_by_match(
keywords, page, page_size, offset, pantry_set, q_param, c,
sensory_exclude=sensory_exclude,
rows = self._fetch_all(
"""
SELECT id, title, category, keywords, ingredient_names,
calories, fat_g, protein_g, sodium_mg
FROM recipes
WHERE id IN (
SELECT rowid FROM recipe_browser_fts
WHERE recipe_browser_fts MATCH ?
)
cols = (
f"SELECT id, title, category, keywords, ingredient_names,"
f" calories, fat_g, protein_g, sodium_mg, directions, sensory_tags FROM {c}recipes"
ORDER BY id ASC
LIMIT ? OFFSET ?
""",
(match_expr, page_size, offset),
)
if keywords is None:
if q_param:
total = self.conn.execute(
f"SELECT COUNT(*) FROM {c}recipes WHERE LOWER(title) LIKE LOWER(?)",
(q_param,),
).fetchone()[0]
rows = self._fetch_all(
f"{cols} WHERE LOWER(title) LIKE LOWER(?) {order_clause} LIMIT ? OFFSET ?",
(q_param, page_size, offset),
)
else:
total = self.conn.execute(f"SELECT COUNT(*) FROM {c}recipes").fetchone()[0]
rows = self._fetch_all(
f"{cols} {order_clause} LIMIT ? OFFSET ?",
(page_size, offset),
)
else:
match_expr = self._browser_fts_query(keywords)
fts_sub = f"id IN (SELECT rowid FROM {c}recipe_browser_fts WHERE recipe_browser_fts MATCH ?)"
if q_param:
total = self.conn.execute(
f"SELECT COUNT(*) FROM {c}recipes WHERE {fts_sub} AND LOWER(title) LIKE LOWER(?)",
(match_expr, q_param),
).fetchone()[0]
rows = self._fetch_all(
f"{cols} WHERE {fts_sub} AND LOWER(title) LIKE LOWER(?) {order_clause} LIMIT ? OFFSET ?",
(match_expr, q_param, page_size, offset),
)
else:
# Reuse cached count — avoids a second index scan on every page turn.
total = self._count_recipes_for_keywords(keywords)
rows = self._fetch_all(
f"{cols} WHERE {fts_sub} {order_clause} LIMIT ? OFFSET ?",
(match_expr, page_size, offset),
)
# Community tag fallback: if FTS found nothing, check whether
# community-tagged recipe IDs exist for this keyword context.
# browse_recipes doesn't know domain/category directly, so the
# fallback is triggered by the caller via community_ids= when needed.
# (See browse_recipes_with_community_fallback in the endpoint layer.)
pantry_set = {p.lower() for p in pantry_items} if pantry_items else None
recipes = []
for r in rows:
# Apply sensory filter -- untagged recipes (empty {}) always pass
if sensory_exclude and not sensory_exclude.is_empty():
if not passes_sensory_filter(r.get("sensory_tags"), sensory_exclude):
continue
entry = {
"id": r["id"],
"title": r["title"],
"category": r["category"],
"match_pct": None,
"id": r["id"],
"title": r["title"],
"category": r["category"],
"match_pct": None,
}
if pantry_set:
names = r.get("ingredient_names") or []
if names:
matched = sum(1 for n in names if n.lower() in pantry_set)
matched = sum(
1 for n in names if n.lower() in pantry_set
)
entry["match_pct"] = round(matched / len(names), 3)
recipes.append(entry)
return {"recipes": recipes, "total": total, "page": page}
def fetch_recipes_by_ids(
self,
recipe_ids: list[int],
pantry_items: list[str] | None = None,
) -> list[dict]:
"""Fetch a specific set of corpus recipes by ID for community tag fallback.
Returns recipes in the same shape as browse_recipes rows, with match_pct
populated when pantry_items are provided.
"""
if not recipe_ids:
return []
c = self._cp
pantry_set = {p.lower() for p in pantry_items} if pantry_items else None
ph = ",".join("?" * len(recipe_ids))
rows = self._fetch_all(
f"SELECT id, title, category, keywords, ingredient_names,"
f" calories, fat_g, protein_g, sodium_mg, directions"
f" FROM {c}recipes WHERE id IN ({ph}) ORDER BY id ASC",
tuple(recipe_ids),
)
result = []
for r in rows:
entry: dict = {
"id": r["id"],
"title": r["title"],
"category": r["category"],
"match_pct": None,
}
entry["directions"] = r.get("directions")
if pantry_set:
names = r.get("ingredient_names") or []
if names:
matched = sum(1 for n in names if n.lower() in pantry_set)
entry["match_pct"] = round(matched / len(names), 3)
result.append(entry)
return result
# How many FTS candidates to fetch before Python-scoring for match sort.
# Large enough to cover several pages with good diversity; small enough
# that json-parsing + dict-lookup stays sub-second even for big categories.
_MATCH_POOL_SIZE = 800
def _browse_by_match(
self,
keywords: list[str] | None,
page: int,
page_size: int,
offset: int,
pantry_set: set[str],
q_param: str | None,
c: str,
sensory_exclude: SensoryExclude | None = None,
) -> dict:
"""Browse recipes sorted by pantry match percentage.
Fetches up to _MATCH_POOL_SIZE FTS candidates, scores each against the
pantry set in Python (fast dict lookup on a bounded list), then sorts
and paginates in-memory. This avoids correlated json_each() subqueries
that are prohibitively slow over 50k+ row result sets.
The reported total is the full FTS count (from cache), not pool size.
"""
import json as _json
pantry_lower = {p.lower() for p in pantry_set}
# ── Fetch candidate pool from FTS ────────────────────────────────────
base_cols = (
f"SELECT r.id, r.title, r.category, r.ingredient_names, r.directions, r.sensory_tags"
f" FROM {c}recipes r"
)
self.conn.row_factory = sqlite3.Row
if keywords is None:
if q_param:
total = self.conn.execute(
f"SELECT COUNT(*) FROM {c}recipes WHERE LOWER(title) LIKE LOWER(?)",
(q_param,),
).fetchone()[0]
rows = self.conn.execute(
f"{base_cols} WHERE LOWER(r.title) LIKE LOWER(?)"
f" ORDER BY r.id ASC LIMIT ?",
(q_param, self._MATCH_POOL_SIZE),
).fetchall()
else:
total = self.conn.execute(
f"SELECT COUNT(*) FROM {c}recipes"
).fetchone()[0]
rows = self.conn.execute(
f"{base_cols} ORDER BY r.id ASC LIMIT ?",
(self._MATCH_POOL_SIZE,),
).fetchall()
else:
match_expr = self._browser_fts_query(keywords)
fts_sub = (
f"r.id IN (SELECT rowid FROM {c}recipe_browser_fts"
f" WHERE recipe_browser_fts MATCH ?)"
)
if q_param:
total = self.conn.execute(
f"SELECT COUNT(*) FROM {c}recipes r"
f" WHERE {fts_sub} AND LOWER(r.title) LIKE LOWER(?)",
(match_expr, q_param),
).fetchone()[0]
rows = self.conn.execute(
f"{base_cols} WHERE {fts_sub} AND LOWER(r.title) LIKE LOWER(?)"
f" ORDER BY r.id ASC LIMIT ?",
(match_expr, q_param, self._MATCH_POOL_SIZE),
).fetchall()
else:
total = self._count_recipes_for_keywords(keywords)
rows = self.conn.execute(
f"{base_cols} WHERE {fts_sub} ORDER BY r.id ASC LIMIT ?",
(match_expr, self._MATCH_POOL_SIZE),
).fetchall()
# ── Score in Python, sort, paginate ──────────────────────────────────
scored = []
for r in rows:
row = dict(r)
# Sensory filter applied before scoring to keep hot path clean
if sensory_exclude and not sensory_exclude.is_empty():
if not passes_sensory_filter(row.get("sensory_tags"), sensory_exclude):
continue
try:
names = _json.loads(row["ingredient_names"] or "[]")
except Exception:
names = []
if names:
matched = sum(1 for n in names if n.lower() in pantry_lower)
match_pct = round(matched / len(names), 3)
else:
match_pct = None
scored.append({
"id": row["id"],
"title": row["title"],
"category": row["category"],
"match_pct": match_pct,
"directions": row.get("directions"),
})
scored.sort(key=lambda r: (-(r["match_pct"] or 0), r["id"]))
page_slice = scored[offset: offset + page_size]
return {"recipes": page_slice, "total": total, "page": page}
def log_browser_telemetry(
self,
domain: str,
@ -1434,12 +1025,6 @@ class Store:
def get_meal_plan(self, plan_id: int) -> dict | None:
return self._fetch_one("SELECT * FROM meal_plans WHERE id = ?", (plan_id,))
def update_meal_plan_types(self, plan_id: int, meal_types: list[str]) -> dict | None:
return self._fetch_one(
"UPDATE meal_plans SET meal_types = ? WHERE id = ? RETURNING *",
(json.dumps(meal_types), plan_id),
)
def list_meal_plans(self) -> list[dict]:
return self._fetch_all("SELECT * FROM meal_plans ORDER BY week_start DESC")
@ -1469,11 +1054,10 @@ class Store:
self.conn.commit()
def get_plan_slots(self, plan_id: int) -> list[dict]:
c = self._cp
return self._fetch_all(
f"""SELECT s.*, r.title AS recipe_title
"""SELECT s.*, r.name AS recipe_title
FROM meal_plan_slots s
LEFT JOIN {c}recipes r ON r.id = s.recipe_id
LEFT JOIN recipes r ON r.id = s.recipe_id
WHERE s.plan_id = ?
ORDER BY s.day_of_week, s.meal_type""",
(plan_id,),
@ -1481,11 +1065,10 @@ class Store:
def get_plan_recipes(self, plan_id: int) -> list[dict]:
"""Return full recipe rows for all recipes assigned to a plan."""
c = self._cp
return self._fetch_all(
f"""SELECT DISTINCT r.*
"""SELECT DISTINCT r.*
FROM meal_plan_slots s
JOIN {c}recipes r ON r.id = s.recipe_id
JOIN recipes r ON r.id = s.recipe_id
WHERE s.plan_id = ? AND s.recipe_id IS NOT NULL""",
(plan_id,),
)
@ -1546,7 +1129,7 @@ class Store:
self.conn.commit()
return self._fetch_one("SELECT * FROM prep_tasks WHERE id = ?", (task_id,))
# ── community ─────────────────────────────────────────────────────────
# ── Community pseudonyms ──────────────────────────────────────────────────
def get_current_pseudonym(self, directus_user_id: str) -> str | None:
"""Return the current community pseudonym for this user, or None if not set."""
@ -1573,141 +1156,3 @@ class Store:
(pseudonym, directus_user_id),
)
self.conn.commit()
# ── Shopping list ─────────────────────────────────────────────────────────
def add_shopping_item(
self,
name: str,
quantity: float | None = None,
unit: str | None = None,
category: str | None = None,
notes: str | None = None,
source: str = "manual",
recipe_id: int | None = None,
sort_order: int = 0,
) -> dict:
return self._insert_returning(
"""INSERT INTO shopping_list_items
(name, quantity, unit, category, notes, source, recipe_id, sort_order)
VALUES (?, ?, ?, ?, ?, ?, ?, ?) RETURNING *""",
(name, quantity, unit, category, notes, source, recipe_id, sort_order),
)
def list_shopping_items(self, include_checked: bool = True) -> list[dict]:
where = "" if include_checked else "WHERE checked = 0"
self.conn.row_factory = sqlite3.Row
rows = self.conn.execute(
f"SELECT * FROM shopping_list_items {where} ORDER BY checked, sort_order, id",
).fetchall()
return [self._row_to_dict(r) for r in rows]
def get_shopping_item(self, item_id: int) -> dict | None:
self.conn.row_factory = sqlite3.Row
row = self.conn.execute(
"SELECT * FROM shopping_list_items WHERE id = ?", (item_id,)
).fetchone()
return self._row_to_dict(row) if row else None
def update_shopping_item(self, item_id: int, **kwargs) -> dict | None:
allowed = {"name", "quantity", "unit", "category", "checked", "notes", "sort_order"}
fields = {k: v for k, v in kwargs.items() if k in allowed and v is not None}
if not fields:
return self.get_shopping_item(item_id)
if "checked" in fields:
fields["checked"] = 1 if fields["checked"] else 0
set_clause = ", ".join(f"{k} = ?" for k in fields)
values = list(fields.values()) + [item_id]
self.conn.execute(
f"UPDATE shopping_list_items SET {set_clause}, updated_at = datetime('now') WHERE id = ?",
values,
)
self.conn.commit()
return self.get_shopping_item(item_id)
def delete_shopping_item(self, item_id: int) -> bool:
cur = self.conn.execute(
"DELETE FROM shopping_list_items WHERE id = ?", (item_id,)
)
self.conn.commit()
return cur.rowcount > 0
def clear_checked_shopping_items(self) -> int:
cur = self.conn.execute("DELETE FROM shopping_list_items WHERE checked = 1")
self.conn.commit()
return cur.rowcount
def clear_all_shopping_items(self) -> int:
cur = self.conn.execute("DELETE FROM shopping_list_items")
self.conn.commit()
return cur.rowcount
# ── Captured products (visual label cache) ────────────────────────────────
def get_captured_product(self, barcode: str) -> dict | None:
"""Look up a locally-captured product by barcode.
Returns the row dict (ingredient_names and allergens already decoded as
lists) or None if the barcode has not been captured yet.
"""
return self._fetch_one(
"SELECT * FROM captured_products WHERE barcode = ?", (barcode,)
)
def save_captured_product(
self,
barcode: str,
*,
product_name: str | None = None,
brand: str | None = None,
serving_size_g: float | None = None,
calories: float | None = None,
fat_g: float | None = None,
saturated_fat_g: float | None = None,
carbs_g: float | None = None,
sugar_g: float | None = None,
fiber_g: float | None = None,
protein_g: float | None = None,
sodium_mg: float | None = None,
ingredient_names: list[str] | None = None,
allergens: list[str] | None = None,
confidence: float | None = None,
confirmed_by_user: bool = True,
source: str = "visual_capture",
) -> dict:
"""Insert or replace a captured product row, returning the saved dict."""
return self._insert_returning(
"""INSERT INTO captured_products
(barcode, product_name, brand, serving_size_g, calories,
fat_g, saturated_fat_g, carbs_g, sugar_g, fiber_g,
protein_g, sodium_mg, ingredient_names, allergens,
confidence, confirmed_by_user, source)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
ON CONFLICT(barcode) DO UPDATE SET
product_name = excluded.product_name,
brand = excluded.brand,
serving_size_g = excluded.serving_size_g,
calories = excluded.calories,
fat_g = excluded.fat_g,
saturated_fat_g = excluded.saturated_fat_g,
carbs_g = excluded.carbs_g,
sugar_g = excluded.sugar_g,
fiber_g = excluded.fiber_g,
protein_g = excluded.protein_g,
sodium_mg = excluded.sodium_mg,
ingredient_names = excluded.ingredient_names,
allergens = excluded.allergens,
confidence = excluded.confidence,
confirmed_by_user = excluded.confirmed_by_user,
source = excluded.source,
captured_at = datetime('now')
RETURNING *""",
(
barcode, product_name, brand, serving_size_g, calories,
fat_g, saturated_fat_g, carbs_g, sugar_g, fiber_g,
protein_g, sodium_mg,
self._dump(ingredient_names or []),
self._dump(allergens or []),
confidence, 1 if confirmed_by_user else 0, source,
),
)

View file

@ -1,9 +1,7 @@
#!/usr/bin/env python
# app/main.py
import asyncio
import logging
import os
from contextlib import asynccontextmanager
from fastapi import FastAPI
@ -13,31 +11,8 @@ from app.api.routes import api_router
from app.core.config import settings
from app.services.meal_plan.affiliates import register_kiwi_programs
# Structured key=value log lines — grep/awk-friendly for log-based analytics.
# Without basicConfig, app-level INFO logs are silently dropped.
logging.basicConfig(level=logging.INFO, format="%(levelname)s:%(name)s: %(message)s")
logger = logging.getLogger(__name__)
_BROWSE_REFRESH_INTERVAL_H = 24
async def _browse_counts_refresh_loop(corpus_path: str) -> None:
"""Refresh browse counts every 24 h while the container is running."""
from app.db.store import _COUNT_CACHE
from app.services.recipe.browse_counts_cache import load_into_memory, refresh
while True:
await asyncio.sleep(_BROWSE_REFRESH_INTERVAL_H * 3600)
try:
logger.info("browse_counts: starting scheduled refresh...")
computed = await asyncio.to_thread(
refresh, corpus_path, settings.BROWSE_COUNTS_PATH
)
load_into_memory(settings.BROWSE_COUNTS_PATH, _COUNT_CACHE, corpus_path)
logger.info("browse_counts: scheduled refresh complete (%d sets)", computed)
except Exception as exc:
logger.warning("browse_counts: scheduled refresh failed: %s", exc)
@asynccontextmanager
async def lifespan(app: FastAPI):
@ -45,36 +20,15 @@ async def lifespan(app: FastAPI):
settings.ensure_dirs()
register_kiwi_programs()
# Initialize community store (fail-soft if COMMUNITY_DB_URL not set)
from app.api.endpoints.community import init_community_store
init_community_store(settings.COMMUNITY_DB_URL)
# Start LLM background task scheduler
from app.tasks.scheduler import get_scheduler
get_scheduler(settings.DB_PATH)
logger.info("Task scheduler started.")
# Initialize community store (no-op if COMMUNITY_DB_URL is not set)
from app.api.endpoints.community import init_community_store
init_community_store(settings.COMMUNITY_DB_URL)
# Browse counts cache — warm in-memory cache from disk, refresh if stale.
# Uses the corpus path the store will attach to at request time.
corpus_path = os.environ.get("RECIPE_DB_PATH", str(settings.DB_PATH))
try:
from app.db.store import _COUNT_CACHE
from app.services.recipe.browse_counts_cache import (
is_stale, load_into_memory, refresh,
)
if is_stale(settings.BROWSE_COUNTS_PATH):
logger.info("browse_counts: cache stale — refreshing in background...")
asyncio.create_task(
asyncio.to_thread(refresh, corpus_path, settings.BROWSE_COUNTS_PATH)
)
else:
load_into_memory(settings.BROWSE_COUNTS_PATH, _COUNT_CACHE, corpus_path)
except Exception as exc:
logger.warning("browse_counts: startup init failed (live FTS fallback active): %s", exc)
# Nightly background refresh loop
asyncio.create_task(_browse_counts_refresh_loop(corpus_path))
yield
# Graceful scheduler shutdown

View file

@ -89,20 +89,9 @@ class InventoryItemUpdate(BaseModel):
unit: Optional[str] = None
location: Optional[str] = None
sublocation: Optional[str] = None
purchase_date: Optional[date] = None
expiration_date: Optional[date] = None
opened_date: Optional[date] = None
status: Optional[str] = None
notes: Optional[str] = None
disposal_reason: Optional[str] = None
class PartialConsumeRequest(BaseModel):
quantity: float = Field(..., gt=0, description="Amount to consume from this item")
class DiscardRequest(BaseModel):
reason: Optional[str] = Field(None, max_length=200)
class InventoryItemResponse(BaseModel):
@ -117,15 +106,8 @@ class InventoryItemResponse(BaseModel):
sublocation: Optional[str]
purchase_date: Optional[str]
expiration_date: Optional[str]
opened_date: Optional[str] = None
opened_expiry_date: Optional[str] = None
secondary_state: Optional[str] = None
secondary_uses: Optional[List[str]] = None
secondary_warning: Optional[str] = None
secondary_discard_signs: Optional[str] = None
status: str
notes: Optional[str]
disposal_reason: Optional[str] = None
source: str
created_at: str
updated_at: str
@ -141,8 +123,6 @@ class BarcodeScanResult(BaseModel):
product: Optional[ProductResponse]
inventory_item: Optional[InventoryItemResponse]
added_to_inventory: bool
needs_manual_entry: bool = False
needs_visual_capture: bool = False # Paid tier offer when no product data found
message: str

View file

@ -1,59 +0,0 @@
"""Pydantic schemas for visual label capture (kiwi#79)."""
from __future__ import annotations
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field
class LabelCaptureResponse(BaseModel):
"""Extraction result returned after the user photographs a nutrition label."""
barcode: str
product_name: Optional[str] = None
brand: Optional[str] = None
serving_size_g: Optional[float] = None
calories: Optional[float] = None
fat_g: Optional[float] = None
saturated_fat_g: Optional[float] = None
carbs_g: Optional[float] = None
sugar_g: Optional[float] = None
fiber_g: Optional[float] = None
protein_g: Optional[float] = None
sodium_mg: Optional[float] = None
ingredient_names: List[str] = Field(default_factory=list)
allergens: List[str] = Field(default_factory=list)
confidence: float = 0.0
needs_review: bool = True # True when confidence < REVIEW_THRESHOLD
class LabelConfirmRequest(BaseModel):
"""User-confirmed extraction to save to the local product cache."""
barcode: str
product_name: Optional[str] = None
brand: Optional[str] = None
serving_size_g: Optional[float] = None
calories: Optional[float] = None
fat_g: Optional[float] = None
saturated_fat_g: Optional[float] = None
carbs_g: Optional[float] = None
sugar_g: Optional[float] = None
fiber_g: Optional[float] = None
protein_g: Optional[float] = None
sodium_mg: Optional[float] = None
ingredient_names: List[str] = Field(default_factory=list)
allergens: List[str] = Field(default_factory=list)
confidence: float = 0.0
# When True the confirmed product is also added to inventory
location: str = "pantry"
quantity: float = 1.0
auto_add: bool = True
class LabelConfirmResponse(BaseModel):
"""Result of confirming a captured product."""
ok: bool
barcode: str
product_id: Optional[int] = None
inventory_item_id: Optional[int] = None
message: str

View file

@ -22,10 +22,6 @@ class CreatePlanRequest(BaseModel):
return v
class UpdatePlanRequest(BaseModel):
meal_types: list[str]
class UpsertSlotRequest(BaseModel):
recipe_id: int | None = None
servings: float = Field(2.0, gt=0)

View file

@ -41,9 +41,6 @@ class RecipeSuggestion(BaseModel):
is_wildcard: bool = False
nutrition: NutritionPanel | None = None
source_url: str | None = None
complexity: str | None = None # 'easy' | 'moderate' | 'involved'
estimated_time_min: int | None = None # derived from step count + method signals
rerank_score: float | None = None # cross-encoder relevance score (paid+ only, None for free tier)
class GroceryLink(BaseModel):
@ -59,19 +56,6 @@ class RecipeResult(BaseModel):
grocery_links: list[GroceryLink] = Field(default_factory=list)
rate_limited: bool = False
rate_limit_count: int = 0
orch_fallback: bool = False # True when orch budget exhausted; fell back to local LLM
class RecipeJobQueued(BaseModel):
job_id: str
status: str = "queued"
class RecipeJobStatus(BaseModel):
job_id: str
status: str
result: RecipeResult | None = None
error: str | None = None
class NutritionFilters(BaseModel):
@ -84,10 +68,6 @@ class NutritionFilters(BaseModel):
class RecipeRequest(BaseModel):
pantry_items: list[str]
# Maps product name → secondary state label for items past nominal expiry
# but still within their secondary use window (e.g. {"Bread": "stale"}).
# Used by the recipe engine to boost recipes suited to those specific states.
secondary_pantry_items: dict[str, str] = Field(default_factory=dict)
level: int = Field(default=1, ge=1, le=4)
constraints: list[str] = Field(default_factory=list)
expiry_first: bool = False
@ -101,76 +81,4 @@ class RecipeRequest(BaseModel):
allergies: list[str] = Field(default_factory=list)
nutrition_filters: NutritionFilters = Field(default_factory=NutritionFilters)
excluded_ids: list[int] = Field(default_factory=list)
exclude_ingredients: list[str] = Field(default_factory=list)
shopping_mode: bool = False
pantry_match_only: bool = False # when True, only return recipes with zero missing ingredients
complexity_filter: str | None = None # 'easy' | 'moderate' | 'involved' — None = any
max_time_min: int | None = None # filter by estimated cooking time ceiling
max_total_min: int | None = None # filter by parsed total time from recipe directions
unit_system: str = "metric" # "metric" | "imperial"
# ── Build Your Own schemas ──────────────────────────────────────────────────
class AssemblyRoleOut(BaseModel):
"""One role slot in a template, as returned by GET /api/recipes/templates."""
display: str
required: bool
keywords: list[str]
hint: str = ""
class AssemblyTemplateOut(BaseModel):
"""One assembly template, as returned by GET /api/recipes/templates."""
id: str # slug, e.g. "burrito_taco"
title: str
icon: str
descriptor: str
role_sequence: list[AssemblyRoleOut]
class RoleCandidateItem(BaseModel):
"""One candidate ingredient for a wizard picker step."""
name: str
in_pantry: bool
tags: list[str] = Field(default_factory=list)
class RoleCandidatesResponse(BaseModel):
"""Response from GET /api/recipes/template-candidates."""
compatible: list[RoleCandidateItem] = Field(default_factory=list)
other: list[RoleCandidateItem] = Field(default_factory=list)
available_tags: list[str] = Field(default_factory=list)
class BuildRequest(BaseModel):
"""Request body for POST /api/recipes/build."""
template_id: str
role_overrides: dict[str, str] = Field(default_factory=dict)
class StreamTokenRequest(BaseModel):
"""Request body for POST /recipes/stream-token.
Pantry items and dietary constraints are fetched from the DB at request
time the client does not supply them here.
"""
level: int = Field(4, ge=3, le=4, description="Recipe level: 3=styled, 4=wildcard")
wildcard_confirmed: bool = Field(False, description="Required true for level 4")
class StreamTokenResponse(BaseModel):
"""Response from POST /recipes/stream-token.
The frontend opens EventSource at stream_url?token=<token> to receive
SSE chunks directly from the coordinator.
"""
stream_url: str
token: str
expires_in_s: int

View file

@ -1,60 +0,0 @@
"""Pydantic schemas for the shopping list endpoints."""
from __future__ import annotations
from typing import Optional
from pydantic import BaseModel, Field
class ShoppingItemCreate(BaseModel):
name: str = Field(..., min_length=1, max_length=200)
quantity: Optional[float] = None
unit: Optional[str] = None
category: Optional[str] = None
notes: Optional[str] = None
source: str = "manual"
recipe_id: Optional[int] = None
sort_order: int = 0
class ShoppingItemUpdate(BaseModel):
name: Optional[str] = Field(None, min_length=1, max_length=200)
quantity: Optional[float] = None
unit: Optional[str] = None
category: Optional[str] = None
checked: Optional[bool] = None
notes: Optional[str] = None
sort_order: Optional[int] = None
class GroceryLinkOut(BaseModel):
ingredient: str
retailer: str
url: str
class ShoppingItemResponse(BaseModel):
id: int
name: str
quantity: Optional[float]
unit: Optional[str]
category: Optional[str]
checked: bool
notes: Optional[str]
source: str
recipe_id: Optional[int]
sort_order: int
created_at: str
updated_at: str
grocery_links: list[GroceryLinkOut] = []
class BulkAddFromRecipeRequest(BaseModel):
recipe_id: int
include_covered: bool = False # if True, add pantry-covered items too
class ConfirmPurchaseRequest(BaseModel):
"""Move a checked item into pantry inventory."""
location: str = "pantry"
quantity: Optional[float] = None # override the list quantity
unit: Optional[str] = None

View file

@ -3,11 +3,6 @@
Business logic services for Kiwi.
"""
__all__ = ["ReceiptService"]
from app.services.receipt_service import ReceiptService
def __getattr__(name: str):
if name == "ReceiptService":
from app.services.receipt_service import ReceiptService
return ReceiptService
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
__all__ = ["ReceiptService"]

View file

@ -1,5 +1,5 @@
# app/services/community/ap_compat.py
# MIT License — AP scaffold only (no actor, inbox, outbox)
# MIT License — AP (ActivityPub) scaffold only (no actor, inbox, outbox)
from __future__ import annotations
@ -9,9 +9,9 @@ from datetime import datetime, timezone
def post_to_ap_json_ld(post: dict, base_url: str) -> dict:
"""Serialize a community post dict to an ActivityPub-compatible JSON-LD Note.
This is a read-only scaffold. No AP actor, inbox, or outbox.
The slug URI is stable so a future full AP implementation can reuse posts
without a DB migration.
This is a read-only scaffold. No AP actor, inbox, or outbox is implemented.
The slug URI is stable so a future full AP implementation can envelope posts
without a database migration.
"""
slug = post["slug"]
published = post.get("published")

View file

@ -5,59 +5,9 @@ from __future__ import annotations
import logging
from circuitforge_core.community import CommunityPost, SharedStore
logger = logging.getLogger(__name__)
class KiwiCommunityStore(SharedStore):
"""Kiwi-specific community store: adds kiwi-domain query methods on top of SharedStore."""
def list_meal_plans(
self,
limit: int = 20,
offset: int = 0,
dietary_tags: list[str] | None = None,
allergen_exclude: list[str] | None = None,
) -> list[CommunityPost]:
return self.list_posts(
limit=limit,
offset=offset,
post_type="plan",
dietary_tags=dietary_tags,
allergen_exclude=allergen_exclude,
source_product="kiwi",
)
def list_outcomes(
self,
limit: int = 20,
offset: int = 0,
post_type: str | None = None,
) -> list[CommunityPost]:
if post_type in ("recipe_success", "recipe_blooper"):
return self.list_posts(
limit=limit,
offset=offset,
post_type=post_type,
source_product="kiwi",
)
success = self.list_posts(
limit=limit,
offset=0,
post_type="recipe_success",
source_product="kiwi",
)
bloopers = self.list_posts(
limit=limit,
offset=0,
post_type="recipe_blooper",
source_product="kiwi",
)
merged = sorted(success + bloopers, key=lambda p: p.published, reverse=True)
return merged[:limit]
def get_or_create_pseudonym(
store,
directus_user_id: str,
@ -77,7 +27,7 @@ def get_or_create_pseudonym(
if not requested_name or not requested_name.strip():
raise ValueError(
"A pseudonym is required for first publish. "
"Pass requested_name with the user's chosen display name."
"Pass requested_name with your chosen display name."
)
name = requested_name.strip()
@ -88,3 +38,71 @@ def get_or_create_pseudonym(
store.set_pseudonym(directus_user_id, name)
return name
try:
from circuitforge_core.community import SharedStore, CommunityPost
class KiwiCommunityStore(SharedStore):
"""Kiwi-specific community store: adds kiwi-domain query methods on top of SharedStore."""
def list_meal_plans(
self,
limit: int = 20,
offset: int = 0,
dietary_tags: list[str] | None = None,
allergen_exclude: list[str] | None = None,
) -> list[CommunityPost]:
return self.list_posts(
limit=limit,
offset=offset,
post_type="plan",
dietary_tags=dietary_tags,
allergen_exclude=allergen_exclude,
source_product="kiwi",
)
def list_outcomes(
self,
limit: int = 20,
offset: int = 0,
post_type: str | None = None,
) -> list[CommunityPost]:
if post_type in ("recipe_success", "recipe_blooper"):
return self.list_posts(
limit=limit, offset=offset,
post_type=post_type, source_product="kiwi",
)
# Fetch both types and merge by published date
success = self.list_posts(
limit=limit, offset=0, post_type="recipe_success", source_product="kiwi",
)
bloopers = self.list_posts(
limit=limit, offset=0, post_type="recipe_blooper", source_product="kiwi",
)
merged = sorted(success + bloopers, key=lambda p: p.published, reverse=True)
return merged[:limit]
except ImportError:
# cf-core community module not yet merged — stub for local dev without community DB
class KiwiCommunityStore: # type: ignore[no-redef]
def __init__(self, *args, **kwargs):
pass
def list_meal_plans(self, **kwargs):
return []
def list_outcomes(self, **kwargs):
return []
def list_posts(self, **kwargs):
return []
def get_post_by_slug(self, slug):
return None
def insert_post(self, post):
return post
def delete_post(self, slug, pseudonym):
return False

View file

@ -38,8 +38,7 @@ _ANIMAL_PRODUCT_KEYWORDS = frozenset([
def _detect_allergens(ingredient_names: list[str]) -> list[str]:
found: set[str] = set()
lowered = [n.lower() for n in ingredient_names]
for ingredient in lowered:
for ingredient in (n.lower() for n in ingredient_names):
for keyword, flag in _ALLERGEN_MAP.items():
if keyword in ingredient:
found.add(flag)
@ -47,9 +46,7 @@ def _detect_allergens(ingredient_names: list[str]) -> list[str]:
def _detect_dietary_tags(ingredient_names: list[str]) -> list[str]:
lowered = [n.lower() for n in ingredient_names]
all_text = " ".join(lowered)
all_text = " ".join(n.lower() for n in ingredient_names)
has_meat = any(k in all_text for k in _MEAT_KEYWORDS)
has_seafood = any(k in all_text for k in _SEAFOOD_KEYWORDS)
has_animal_products = any(k in all_text for k in _ANIMAL_PRODUCT_KEYWORDS)
@ -86,22 +83,18 @@ def compute_snapshot(recipe_ids: list[int], store) -> ElementSnapshot:
Averages numeric scores across all recipes. Unions allergen flags and dietary tags.
Call at publish time only snapshot is stored denormalized in community_posts.
"""
_empty = ElementSnapshot(
seasoning_score=0.0, richness_score=0.0, brightness_score=0.0,
depth_score=0.0, aroma_score=0.0, structure_score=0.0,
texture_profile="", dietary_tags=(), allergen_flags=(),
flavor_molecules=(), fat_pct=None, protein_pct=None, moisture_pct=None,
)
if not recipe_ids:
return ElementSnapshot(
seasoning_score=0.0, richness_score=0.0, brightness_score=0.0,
depth_score=0.0, aroma_score=0.0, structure_score=0.0,
texture_profile="", dietary_tags=(), allergen_flags=(),
flavor_molecules=(), fat_pct=None, protein_pct=None, moisture_pct=None,
)
return _empty
rows = store.get_recipes_by_ids(recipe_ids)
if not rows:
return ElementSnapshot(
seasoning_score=0.0, richness_score=0.0, brightness_score=0.0,
depth_score=0.0, aroma_score=0.0, structure_score=0.0,
texture_profile="", dietary_tags=(), allergen_flags=(),
flavor_molecules=(), fat_pct=None, protein_pct=None, moisture_pct=None,
)
return _empty
def _avg(field: str) -> float:
vals = [r.get(field) or 0.0 for r in rows]
@ -110,16 +103,12 @@ def compute_snapshot(recipe_ids: list[int], store) -> ElementSnapshot:
all_ingredients: list[str] = []
for r in rows:
names = r.get("ingredient_names") or []
all_ingredients.extend(names if isinstance(names, list) else [])
if isinstance(names, list):
all_ingredients.extend(names)
allergens = _detect_allergens(all_ingredients)
dietary = _detect_dietary_tags(all_ingredients)
texture = rows[0].get("texture_profile") or ""
fat_vals = [r.get("fat") for r in rows if r.get("fat") is not None]
prot_vals = [r.get("protein") for r in rows if r.get("protein") is not None]
moist_vals = [r.get("moisture") for r in rows if r.get("moisture") is not None]
fat_vals = [r["fat"] for r in rows if r.get("fat") is not None]
prot_vals = [r["protein"] for r in rows if r.get("protein") is not None]
moist_vals = [r["moisture"] for r in rows if r.get("moisture") is not None]
return ElementSnapshot(
seasoning_score=_avg("seasoning_score"),
@ -128,10 +117,10 @@ def compute_snapshot(recipe_ids: list[int], store) -> ElementSnapshot:
depth_score=_avg("depth_score"),
aroma_score=_avg("aroma_score"),
structure_score=_avg("structure_score"),
texture_profile=texture,
dietary_tags=tuple(dietary),
allergen_flags=tuple(allergens),
flavor_molecules=(),
texture_profile=rows[0].get("texture_profile") or "",
dietary_tags=tuple(_detect_dietary_tags(all_ingredients)),
allergen_flags=tuple(_detect_allergens(all_ingredients)),
flavor_molecules=(), # deferred — FlavorGraph ticket
fat_pct=(sum(fat_vals) / len(fat_vals)) if fat_vals else None,
protein_pct=(sum(prot_vals) / len(prot_vals)) if prot_vals else None,
moisture_pct=(sum(moist_vals) / len(moist_vals)) if moist_vals else None,

View file

@ -1,72 +1,111 @@
# app/services/community/mdns.py
# MIT License
# mDNS advertisement for Kiwi instances on the local network.
# Advertises _kiwi._tcp.local so other Kiwi instances (and discovery apps)
# can find this one without manual configuration.
#
# Opt-in only: enabled=False by default. Users are prompted on first community
# tab access. Never advertised without explicit consent (a11y requirement).
from __future__ import annotations
import logging
import socket
from typing import Any
logger = logging.getLogger(__name__)
# Import deferred to avoid hard failure when zeroconf is not installed
# Deferred import — avoid hard failure when zeroconf is not installed.
try:
from zeroconf import ServiceInfo, Zeroconf
_ZEROCONF_AVAILABLE = True
except ImportError:
except ImportError: # pragma: no cover
_ZEROCONF_AVAILABLE = False
class KiwiMDNS:
"""Advertise this Kiwi instance on the LAN via mDNS (_kiwi._tcp.local).
"""Context manager that advertises this Kiwi instance via mDNS (_kiwi._tcp.local).
Defaults to disabled (enabled=False). User must explicitly opt in via the
Settings page. This matches the CF a11y requirement: no surprise broadcasting.
Defaults to disabled. User must explicitly opt in via Settings.
feed_url is broadcast in the TXT record so peer instances know where to fetch posts.
Usage:
mdns = KiwiMDNS(enabled=settings.MDNS_ENABLED, port=settings.PORT,
feed_url=f"http://{hostname}:{settings.PORT}/api/v1/community/local-feed")
mdns = KiwiMDNS(
enabled=settings.MDNS_ENABLED,
port=8512,
feed_url="http://10.0.0.5:8512/api/v1/community/local-feed",
)
mdns.start() # in lifespan startup
mdns.stop() # in lifespan shutdown
"""
SERVICE_TYPE = "_kiwi._tcp.local."
def __init__(self, enabled: bool, port: int, feed_url: str) -> None:
self._enabled = enabled
def __init__(
self,
port: int = 8512,
name: str | None = None,
feed_url: str = "",
enabled: bool = False,
) -> None:
self._port = port
self._name = name or f"kiwi-{socket.gethostname()}"
self._feed_url = feed_url
self._zc: "Zeroconf | None" = None
self._info: "ServiceInfo | None" = None
self._enabled = enabled
self._zc: Any = None
self._info: Any = None
def start(self) -> None:
if not self._enabled:
logger.debug("mDNS advertisement disabled (user has not opted in)")
return
if not _ZEROCONF_AVAILABLE:
logger.warning("zeroconf package not installed — mDNS advertisement unavailable")
logger.info("mDNS advertisement disabled (user opt-in required)")
return
try:
local_ip = _get_local_ip()
props = {b"product": b"kiwi", b"version": b"1"}
if self._feed_url:
props[b"feed"] = self._feed_url.encode()
hostname = socket.gethostname()
service_name = f"kiwi-{hostname}.{self.SERVICE_TYPE}"
self._info = ServiceInfo(
type_=self.SERVICE_TYPE,
name=service_name,
port=self._port,
properties={
b"feed_url": self._feed_url.encode(),
b"version": b"1",
},
addresses=[socket.inet_aton("127.0.0.1")],
)
self._zc = Zeroconf()
self._zc.register_service(self._info)
logger.info("mDNS: advertising %s on port %d", service_name, self._port)
self._info = ServiceInfo(
type_=self.SERVICE_TYPE,
name=f"{self._name}.{self.SERVICE_TYPE}",
addresses=[socket.inet_aton(local_ip)],
port=self._port,
properties=props,
server=f"{socket.gethostname()}.local.",
)
self._zc = Zeroconf()
self._zc.register_service(self._info)
logger.info("mDNS: advertising %s on %s:%d", self._name, local_ip, self._port)
except Exception as exc:
logger.warning("mDNS advertisement failed (non-fatal): %s", exc)
self._zc = None
self._info = None
def stop(self) -> None:
if self._zc is None or self._info is None:
return
self._zc.unregister_service(self._info)
self._zc.close()
self._zc = None
self._info = None
logger.info("mDNS: advertisement stopped")
if self._zc and self._info:
try:
self._zc.unregister_service(self._info)
self._zc.close()
logger.info("mDNS: unregistered %s", self._name)
except Exception as exc:
logger.warning("mDNS unregister failed (non-fatal): %s", exc)
finally:
self._zc = None
self._info = None
def __enter__(self) -> "KiwiMDNS":
self.start()
return self
def __exit__(self, *_: object) -> None:
self.stop()
def _get_local_ip() -> str:
"""Return the primary non-loopback IPv4 address of this host."""
try:
with socket.socket(socket.AF_INET, socket.SOCK_DGRAM) as s:
s.connect(("8.8.8.8", 80))
return s.getsockname()[0]
except OSError:
return "127.0.0.1"

View file

@ -1,94 +0,0 @@
"""cf-orch coordinator proxy client.
Calls the coordinator's /proxy/authorize endpoint to obtain a one-time
stream URL + token for LLM streaming. Always raises CoordinatorError on
failure callers decide how to handle it (stream-token endpoint returns
503 or 403 as appropriate).
"""
from __future__ import annotations
import logging
import os
from dataclasses import dataclass
import httpx
log = logging.getLogger(__name__)
class CoordinatorError(Exception):
"""Raised when the coordinator returns an error or is unreachable."""
def __init__(self, message: str, status_code: int = 503):
super().__init__(message)
self.status_code = status_code
@dataclass(frozen=True)
class StreamTokenResult:
stream_url: str
token: str
expires_in_s: int
def _coordinator_url() -> str:
return os.environ.get("COORDINATOR_URL", "http://10.1.10.71:7700")
def _product_key() -> str:
return os.environ.get("COORDINATOR_KIWI_KEY", "")
async def coordinator_authorize(
prompt: str,
caller: str = "kiwi-recipe",
ttl_s: int = 300,
) -> StreamTokenResult:
"""Call POST /proxy/authorize on the coordinator.
Returns a StreamTokenResult with the stream URL and one-time token.
Raises CoordinatorError on any failure (network, auth, capacity).
"""
url = f"{_coordinator_url()}/proxy/authorize"
key = _product_key()
if not key:
raise CoordinatorError(
"COORDINATOR_KIWI_KEY env var is not set — streaming unavailable",
status_code=503,
)
payload = {
"product": "kiwi",
"product_key": key,
"caller": caller,
"prompt": prompt,
"params": {},
"ttl_s": ttl_s,
}
try:
async with httpx.AsyncClient(timeout=10.0) as client:
resp = await client.post(url, json=payload)
except httpx.RequestError as exc:
log.warning("coordinator_authorize network error: %s", exc)
raise CoordinatorError(f"Coordinator unreachable: {exc}", status_code=503)
if resp.status_code == 401:
raise CoordinatorError("Invalid product key", status_code=401)
if resp.status_code == 429:
raise CoordinatorError("Too many concurrent streams", status_code=429)
if resp.status_code == 503:
raise CoordinatorError("No GPU available for streaming", status_code=503)
if not resp.is_success:
raise CoordinatorError(
f"Coordinator error {resp.status_code}: {resp.text[:200]}",
status_code=503,
)
data = resp.json()
# Use public_stream_url if coordinator provides it (cloud mode), else stream_url
stream_url = data.get("public_stream_url") or data["stream_url"]
return StreamTokenResult(
stream_url=stream_url,
token=data["token"],
expires_in_s=data["expires_in_s"],
)

View file

@ -116,270 +116,6 @@ class ExpirationPredictor:
'prepared_foods': {'fridge': 4, 'freezer': 90},
}
# Secondary shelf life in days after a package is opened.
# Sources: USDA FoodKeeper app, FDA consumer guides.
# Only categories where opening significantly shortens shelf life are listed.
# Items not listed default to None (no secondary window tracked).
SHELF_LIFE_AFTER_OPENING: dict[str, int] = {
# Dairy — once opened, clock ticks fast
'dairy': 5,
'milk': 5,
'cream': 3,
'yogurt': 7,
'cheese': 14,
'butter': 30,
# Condiments — refrigerated after opening
'condiments': 30,
'ketchup': 30,
'mustard': 30,
'mayo': 14,
'salad_dressing': 30,
'soy_sauce': 90,
# Canned goods — once opened, very short
'canned_goods': 4,
# Beverages
'juice': 7,
'soda': 4,
# Bread / Bakery
'bread': 5,
'bakery': 3,
# Produce
'leafy_greens': 3,
'berries': 3,
# Pantry staples (open bag)
'chips': 14,
'cookies': 14,
'cereal': 30,
'flour': 90,
}
# Post-expiry secondary use window.
# These are NOT spoilage extensions — they describe a qualitative state
# change where the ingredient is specifically suited for certain preparations.
# Sources: USDA FoodKeeper, food science, culinary tradition.
#
# Fields:
# window_days — days past nominal expiry still usable in secondary state
# label — short UI label for the state
# uses — recipe contexts suited to this state (shown in UI)
# warning — safety note, calm tone, None if none needed
# discard_signs — qualitative signs the item has gone past the secondary window
# constraints_exclude — dietary constraint labels that suppress this entry entirely
# (e.g. alcohol-containing items suppressed for halal/alcohol-free)
SECONDARY_WINDOW: dict[str, dict] = {
'bread': {
'window_days': 5,
'label': 'stale',
'uses': ['croutons', 'stuffing', 'bread pudding', 'French toast', 'panzanella'],
'warning': 'Check for mold before use — discard if any is visible.',
'discard_signs': 'Visible mold (any colour), or unpleasant smell beyond dry/yeasty.',
'constraints_exclude': [],
},
'bakery': {
'window_days': 3,
'label': 'day-old',
'uses': ['French toast', 'bread pudding', 'crumbles', 'trifle base', 'cake pops', 'streusel topping', 'bread crumbs'],
'warning': 'Check for mold before use — discard if any is visible.',
'discard_signs': 'Visible mold, sliminess, or strong sour smell.',
'constraints_exclude': [],
},
'bananas': {
'window_days': 5,
'label': 'overripe',
'uses': ['banana bread', 'smoothies', 'pancakes', 'muffins'],
'warning': None,
'discard_signs': 'Leaking liquid, fermented smell, or mold on skin.',
'constraints_exclude': [],
},
'milk': {
'window_days': 3,
'label': 'sour',
'uses': ['pancakes', 'scones', 'waffles', 'muffins', 'quick breads', 'béchamel', 'baked mac and cheese'],
'warning': 'Use only in cooked recipes — do not drink.',
'discard_signs': 'Chunky texture, strong unpleasant smell beyond tangy, or visible separation with grey colour.',
'constraints_exclude': [],
},
'dairy': {
'window_days': 2,
'label': 'sour',
'uses': ['pancakes', 'scones', 'quick breads', 'muffins', 'waffles'],
'warning': 'Use only in cooked recipes — do not drink.',
'discard_signs': 'Strong unpleasant smell, unusual colour, or chunky texture.',
'constraints_exclude': [],
},
'cheese': {
'window_days': 14,
'label': 'rind-ready',
'uses': ['parmesan broth', 'minestrone', 'ribollita', 'risotto', 'polenta', 'bean soups', 'gratins'],
'warning': None,
'discard_signs': 'Soft or wet texture on hard cheese, pink or black mold (white/green surface mold on hard cheese can be cut off with 1cm margin).',
'constraints_exclude': [],
},
'rice': {
'window_days': 2,
'label': 'day-old',
'uses': ['fried rice', 'onigiri', 'rice porridge', 'congee', 'arancini', 'stuffed peppers', 'rice fritters'],
'warning': 'Refrigerate immediately after cooking — do not leave at room temp.',
'discard_signs': 'Slimy texture, unusual smell, or more than 4 days since cooking.',
'constraints_exclude': [],
},
'tortillas': {
'window_days': 5,
'label': 'stale',
'uses': ['chilaquiles', 'migas', 'tortilla soup', 'casserole'],
'warning': 'Check for mold, especially if stored in a sealed bag — discard if any is visible.',
'discard_signs': 'Visible mold (check seams and edges), or strong sour smell.',
'constraints_exclude': [],
},
# ── New entries ──────────────────────────────────────────────────────
'apples': {
'window_days': 7,
'label': 'soft',
'uses': ['applesauce', 'apple butter', 'baked apples', 'apple crisp', 'smoothies', 'chutney'],
'warning': None,
'discard_signs': 'Large bruised areas with fermented smell, visible mold, or liquid leaking from skin.',
'constraints_exclude': [],
},
'leafy_greens': {
'window_days': 2,
'label': 'wilting',
'uses': ['sautéed greens', 'soups', 'smoothies', 'frittata', 'pasta add-in', 'stir fry'],
'warning': None,
'discard_signs': 'Slimy texture, strong unpleasant smell, or yellowed and mushy leaves.',
'constraints_exclude': [],
},
'tomatoes': {
'window_days': 4,
'label': 'soft',
'uses': ['roasted tomatoes', 'tomato sauce', 'shakshuka', 'bruschetta', 'soup', 'salsa'],
'warning': None,
'discard_signs': 'Broken skin with liquid pooling, mold, or fermented smell.',
'constraints_exclude': [],
},
'cooked_pasta': {
'window_days': 3,
'label': 'day-old',
'uses': ['pasta frittata', 'pasta salad', 'baked pasta', 'soup add-in', 'fried pasta cakes'],
'warning': 'Refrigerate within 2 hours of cooking.',
'discard_signs': 'Slimy texture, off smell, or more than 4 days since cooking.',
'constraints_exclude': [],
},
'cooked_potatoes': {
'window_days': 3,
'label': 'day-old',
'uses': ['potato pancakes', 'hash browns', 'potato soup', 'gnocchi', 'twice-baked potatoes', 'croquettes'],
'warning': 'Refrigerate within 2 hours of cooking.',
'discard_signs': 'Slimy texture, off smell, or more than 4 days since cooking.',
'constraints_exclude': [],
},
'yogurt': {
'window_days': 7,
'label': 'tangy',
'uses': ['marinades', 'flatbreads', 'smoothies', 'tzatziki', 'baked goods', 'salad dressings'],
'warning': None,
'discard_signs': 'Pink or orange discolouration, visible mold, or strongly unpleasant smell (not just tangy).',
'constraints_exclude': [],
},
'cream': {
'window_days': 2,
'label': 'sour',
'uses': ['soups', 'sauces', 'scones', 'quick breads', 'mashed potatoes'],
'warning': 'Use in cooked recipes only. Discard if the smell is strongly unpleasant rather than tangy.',
'discard_signs': 'Strong unpleasant smell beyond tangy, unusual colour, or chunky texture.',
'constraints_exclude': [],
},
'wine': {
'window_days': 4,
'label': 'open',
'uses': ['pan sauces', 'braises', 'risotto', 'marinades', 'poaching liquid', 'wine reduction'],
'warning': None,
'discard_signs': 'Strong vinegar smell (still usable in braises/marinades), or visible cloudiness with off-smell.',
'constraints_exclude': ['halal', 'alcohol-free'],
},
'cooked_beans': {
'window_days': 3,
'label': 'day-old',
'uses': ['refried beans', 'bean soup', 'bean fritters', 'hummus', 'bean dip', 'grain bowls'],
'warning': 'Refrigerate within 2 hours of cooking.',
'discard_signs': 'Slimy texture, off smell, or more than 4 days since cooking.',
'constraints_exclude': [],
},
'cooked_meat': {
'window_days': 2,
'label': 'leftover',
'uses': ['grain bowls', 'tacos', 'soups', 'fried rice', 'sandwiches', 'hash', 'pasta add-in'],
'warning': 'Refrigerate within 2 hours of cooking.',
'discard_signs': 'Off smell, slimy texture, or more than 34 days since cooking.',
'constraints_exclude': [],
},
}
def days_after_opening(self, category: str | None) -> int | None:
"""Return days of shelf life remaining once a package is opened.
Returns None if the category is unknown or not tracked after opening
(e.g. frozen items, raw meat category check irrelevant once opened).
"""
if not category:
return None
return self.SHELF_LIFE_AFTER_OPENING.get(category.lower())
def secondary_state(
self, category: str | None, expiry_date: str | None
) -> dict | None:
"""Return secondary use info if the item is in its post-expiry secondary window.
Returns a dict with label, uses, warning, discard_signs, constraints_exclude,
days_past, and window_days when the item is past its nominal expiry date but
still within the secondary use window.
Returns None in all other cases (unknown category, no window defined, not yet
expired, or past the secondary window).
Callers should apply constraints_exclude against user dietary constraints
and suppress the result entirely if any excluded constraint is active.
See filter_secondary_by_constraints().
"""
if not category or not expiry_date:
return None
entry = self.SECONDARY_WINDOW.get(category.lower())
if not entry:
return None
try:
from datetime import date
today = date.today()
exp = date.fromisoformat(expiry_date)
days_past = (today - exp).days
if 0 <= days_past <= entry['window_days']:
return {
'label': entry['label'],
'uses': list(entry['uses']),
'warning': entry['warning'],
'discard_signs': entry.get('discard_signs'),
'constraints_exclude': list(entry.get('constraints_exclude') or []),
'days_past': days_past,
'window_days': entry['window_days'],
}
except ValueError:
pass
return None
@staticmethod
def filter_secondary_by_constraints(
sec: dict | None,
user_constraints: list[str],
) -> dict | None:
"""Suppress secondary state entirely if any excluded constraint is active.
Call after secondary_state() when user dietary constraints are available.
Returns sec unchanged when no constraints match, or None when suppressed.
"""
if sec is None:
return None
excluded = sec.get('constraints_exclude') or []
if any(c.lower() in [e.lower() for e in excluded] for c in user_constraints):
return None
return sec
# Keyword lists are checked in declaration order — most specific first.
# Rules:
# - canned/processed goods BEFORE raw-meat terms (canned chicken != raw chicken)

View file

@ -1,80 +0,0 @@
"""Heimdall cf-orch budget client.
Calls Heimdall's /orch/* endpoints to gate and record cf-orch usage for
lifetime/founders license holders. Always fails open on network errors
a Heimdall outage should never block the user.
"""
from __future__ import annotations
import logging
import os
import requests
log = logging.getLogger(__name__)
HEIMDALL_URL: str = os.environ.get("HEIMDALL_URL", "https://license.circuitforge.tech")
HEIMDALL_ADMIN_TOKEN: str = os.environ.get("HEIMDALL_ADMIN_TOKEN", "")
def _headers() -> dict[str, str]:
if HEIMDALL_ADMIN_TOKEN:
return {"Authorization": f"Bearer {HEIMDALL_ADMIN_TOKEN}"}
return {}
def check_orch_budget(key_display: str, product: str) -> dict:
"""Call POST /orch/check and return the response dict.
On any error (network, auth, etc.) returns a permissive dict so the
caller can proceed without blocking the user.
"""
try:
resp = requests.post(
f"{HEIMDALL_URL}/orch/check",
json={"key_display": key_display, "product": product},
headers=_headers(),
timeout=5,
)
if resp.ok:
return resp.json()
log.warning("Heimdall orch/check returned %s for key %s", resp.status_code, key_display[:12])
except Exception as exc:
log.warning("Heimdall orch/check failed (fail-open): %s", exc)
# Fail open — Heimdall outage must never block the user
return {
"allowed": True,
"calls_used": 0,
"calls_total": 0,
"topup_calls": 0,
"period_start": "",
"resets_on": "",
}
def get_orch_usage(key_display: str, product: str) -> dict:
"""Call GET /orch/usage and return the response dict.
Returns zeros on error (non-blocking).
"""
try:
resp = requests.get(
f"{HEIMDALL_URL}/orch/usage",
params={"key_display": key_display, "product": product},
headers=_headers(),
timeout=5,
)
if resp.ok:
return resp.json()
log.warning("Heimdall orch/usage returned %s", resp.status_code)
except Exception as exc:
log.warning("Heimdall orch/usage failed: %s", exc)
return {
"calls_used": 0,
"topup_calls": 0,
"calls_total": 0,
"period_start": "",
"resets_on": "",
}

View file

@ -1,140 +0,0 @@
"""Visual label capture service for unenriched products (kiwi#79).
Wraps the cf-core VisionRouter to extract structured nutrition data from a
photographed nutrition facts panel. When the VisionRouter is not yet wired
(NotImplementedError) the service falls back to a mock extraction so the
barcode scan flow can be exercised end-to-end in development.
JSON contract returned by the vision model (and mock):
{
"product_name": str | null,
"brand": str | null,
"serving_size_g": number | null,
"calories": number | null,
"fat_g": number | null,
"saturated_fat_g": number | null,
"carbs_g": number | null,
"sugar_g": number | null,
"fiber_g": number | null,
"protein_g": number | null,
"sodium_mg": number | null,
"ingredient_names": [str],
"allergens": [str],
"confidence": number (0.01.0)
}
"""
from __future__ import annotations
import json
import logging
import os
from typing import Any
log = logging.getLogger(__name__)
# Confidence below this threshold surfaces amber highlights in the UI.
REVIEW_THRESHOLD = 0.7
_MOCK_EXTRACTION: dict[str, Any] = {
"product_name": "Unknown Product",
"brand": None,
"serving_size_g": None,
"calories": None,
"fat_g": None,
"saturated_fat_g": None,
"carbs_g": None,
"sugar_g": None,
"fiber_g": None,
"protein_g": None,
"sodium_mg": None,
"ingredient_names": [],
"allergens": [],
"confidence": 0.0,
}
_EXTRACTION_PROMPT = """You are reading a nutrition facts label photograph.
Extract the following fields as a JSON object with no extra text:
{
"product_name": <product name or null>,
"brand": <brand name or null>,
"serving_size_g": <serving size in grams as a number or null>,
"calories": <calories per serving as a number or null>,
"fat_g": <total fat grams or null>,
"saturated_fat_g": <saturated fat grams or null>,
"carbs_g": <total carbohydrates grams or null>,
"sugar_g": <sugars grams or null>,
"fiber_g": <dietary fiber grams or null>,
"protein_g": <protein grams or null>,
"sodium_mg": <sodium milligrams or null>,
"ingredient_names": [list of individual ingredients as strings],
"allergens": [list of allergens explicitly stated on label],
"confidence": <your confidence this extraction is correct, 0.0 to 1.0>
}
Use null for any field you cannot read clearly. Do not guess values.
Respond with JSON only."""
def extract_label(image_bytes: bytes) -> dict[str, Any]:
"""Run vision model extraction on raw label image bytes.
Returns a dict matching the nutrition JSON contract above.
Falls back to a zero-confidence mock if the VisionRouter is not yet
implemented (stub) or if the model returns unparseable output.
"""
# Allow unit tests to bypass the vision model entirely.
if os.environ.get("KIWI_LABEL_CAPTURE_MOCK") == "1":
log.debug("label_capture: mock mode active")
return dict(_MOCK_EXTRACTION)
try:
from circuitforge_core.vision import caption as vision_caption
result = vision_caption(image_bytes, prompt=_EXTRACTION_PROMPT)
raw = result.caption or ""
return _parse_extraction(raw)
except Exception as exc:
log.warning("label_capture: extraction failed (%s) — returning mock extraction", exc)
return dict(_MOCK_EXTRACTION)
def _parse_extraction(raw: str) -> dict[str, Any]:
"""Parse the JSON string returned by the vision model.
Strips markdown code fences if present. Validates required shape.
Returns the mock on any parse error.
"""
text = raw.strip()
if text.startswith("```"):
# Strip ```json ... ``` fences
lines = text.splitlines()
text = "\n".join(lines[1:-1] if lines[-1].strip() == "```" else lines[1:])
try:
data = json.loads(text)
except json.JSONDecodeError as exc:
log.warning("label_capture: could not parse vision response: %s", exc)
return dict(_MOCK_EXTRACTION)
if not isinstance(data, dict):
log.warning("label_capture: vision response is not a dict")
return dict(_MOCK_EXTRACTION)
# Normalise list fields — model may return None instead of []
for list_key in ("ingredient_names", "allergens"):
if not isinstance(data.get(list_key), list):
data[list_key] = []
# Clamp confidence to [0, 1]
confidence = data.get("confidence")
if not isinstance(confidence, (int, float)):
confidence = 0.0
data["confidence"] = max(0.0, min(1.0, float(confidence)))
return data
def needs_review(extraction: dict[str, Any]) -> bool:
"""Return True when the extraction confidence is below REVIEW_THRESHOLD."""
return float(extraction.get("confidence", 0.0)) < REVIEW_THRESHOLD

View file

@ -15,73 +15,64 @@ logger = logging.getLogger(__name__)
class OpenFoodFactsService:
"""
Service for interacting with the Open*Facts family of databases.
Service for interacting with the OpenFoodFacts API.
Primary: OpenFoodFacts (food products).
Fallback chain: Open Beauty Facts (personal care) Open Products Facts (household).
All three databases share the same API path and JSON format.
OpenFoodFacts is a free, open database of food products with
ingredients, allergens, and nutrition facts.
"""
BASE_URL = "https://world.openfoodfacts.org/api/v2"
USER_AGENT = "Kiwi/0.1.0 (https://circuitforge.tech)"
# Fallback databases tried in order when OFFs returns no match.
# Same API format as OFFs — only the host differs.
_FALLBACK_DATABASES = [
"https://world.openbeautyfacts.org/api/v2",
"https://world.openproductsfacts.org/api/v2",
]
async def _lookup_in_database(
self, barcode: str, base_url: str, client: httpx.AsyncClient
) -> Optional[Dict[str, Any]]:
"""Try one Open*Facts database using an existing client. Returns parsed product dict or None."""
try:
response = await client.get(
f"{base_url}/product/{barcode}.json",
headers={"User-Agent": self.USER_AGENT},
timeout=10.0,
)
if response.status_code == 404:
return None
response.raise_for_status()
data = response.json()
if data.get("status") != 1:
return None
return self._parse_product_data(data, barcode)
except httpx.HTTPError as e:
logger.debug("HTTP error for %s at %s: %s", barcode, base_url, e)
return None
except Exception as e:
logger.debug("Lookup failed for %s at %s: %s", barcode, base_url, e)
return None
async def lookup_product(self, barcode: str) -> Optional[Dict[str, Any]]:
"""
Look up a product by barcode, trying OFFs then fallback databases.
A single httpx.AsyncClient is created for the whole lookup chain so that
connection pooling and TLS session reuse apply across all database attempts.
Look up a product by barcode in the OpenFoodFacts database.
Args:
barcode: UPC/EAN barcode (8-13 digits)
Returns:
Dictionary with product information, or None if not found in any database.
Dictionary with product information, or None if not found
Example response:
{
"name": "Organic Milk",
"brand": "Horizon",
"categories": ["Dairy", "Milk"],
"image_url": "https://...",
"nutrition_data": {...},
"raw_data": {...} # Full API response
}
"""
async with httpx.AsyncClient() as client:
result = await self._lookup_in_database(barcode, self.BASE_URL, client)
if result:
return result
try:
async with httpx.AsyncClient() as client:
url = f"{self.BASE_URL}/product/{barcode}.json"
for db_url in self._FALLBACK_DATABASES:
result = await self._lookup_in_database(barcode, db_url, client)
if result:
logger.info("Barcode %s found in fallback database: %s", barcode, db_url)
return result
response = await client.get(
url,
headers={"User-Agent": self.USER_AGENT},
timeout=10.0,
)
logger.info("Barcode %s not found in any Open*Facts database", barcode)
return None
if response.status_code == 404:
logger.info(f"Product not found in OpenFoodFacts: {barcode}")
return None
response.raise_for_status()
data = response.json()
if data.get("status") != 1:
logger.info(f"Product not found in OpenFoodFacts: {barcode}")
return None
return self._parse_product_data(data, barcode)
except httpx.HTTPError as e:
logger.error(f"HTTP error looking up barcode {barcode}: {e}")
return None
except Exception as e:
logger.error(f"Error looking up barcode {barcode}: {e}")
return None
def _parse_product_data(self, data: Dict[str, Any], barcode: str) -> Dict[str, Any]:
"""
@ -123,9 +114,6 @@ class OpenFoodFactsService:
allergens = product.get("allergens_tags", [])
labels = product.get("labels_tags", [])
# Pack size detection: prefer explicit unit_count, fall back to serving count
pack_quantity, pack_unit = self._extract_pack_size(product)
return {
"name": name,
"brand": brand,
@ -136,47 +124,9 @@ class OpenFoodFactsService:
"nutrition_data": nutrition_data,
"allergens": allergens,
"labels": labels,
"pack_quantity": pack_quantity,
"pack_unit": pack_unit,
"raw_data": product, # Store full response for debugging
}
def _extract_pack_size(self, product: Dict[str, Any]) -> tuple[float | None, str | None]:
"""Return (quantity, unit) for multi-pack products, or (None, None).
OFFs fields tried in order:
1. `number_of_units` (explicit count, highest confidence)
2. `serving_quantity` + `product_quantity_unit` (e.g. 6 x 150g yoghurt)
3. Parse `quantity` string like "4 x 113 g" or "6 pack"
Returns None, None when data is absent, ambiguous, or single-unit.
"""
import re
# Field 1: explicit unit count
unit_count = product.get("number_of_units")
if unit_count:
try:
n = float(unit_count)
if n > 1:
return n, product.get("serving_size_unit") or "unit"
except (ValueError, TypeError):
pass
# Field 2: parse quantity string for "N x ..." pattern
qty_str = product.get("quantity", "")
if qty_str:
m = re.match(r"^(\d+(?:\.\d+)?)\s*[xX×]\s*", qty_str.strip())
if m:
n = float(m.group(1))
if n > 1:
# Try to get a sensible sub-unit label from the rest
rest = qty_str[m.end():].strip()
unit_label = re.sub(r"[\d.,\s]+", "", rest).strip()[:20] or "unit"
return n, unit_label
return None, None
def _extract_nutrition_data(self, product: Dict[str, Any]) -> Dict[str, Any]:
"""
Extract nutrition facts from product data.

View file

@ -42,21 +42,11 @@ class AssemblyRole:
class AssemblyTemplate:
"""A template assembly dish."""
id: int
slug: str # URL-safe identifier, e.g. "burrito_taco"
icon: str # emoji
descriptor: str # one-line description shown in template grid
title: str
required: list[AssemblyRole]
optional: list[AssemblyRole]
directions: list[str]
notes: str = ""
# Per-role hints shown in the wizard picker header
# keys match role.display values; missing keys fall back to ""
role_hints: dict[str, str] = None # type: ignore[assignment]
def __post_init__(self) -> None:
if self.role_hints is None:
self.role_hints = {}
def _matches_role(role: AssemblyRole, pantry_set: set[str]) -> list[str]:
@ -148,9 +138,6 @@ def _personalized_title(tmpl: AssemblyTemplate, pantry_set: set[str], seed: int)
ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
AssemblyTemplate(
id=-1,
slug="burrito_taco",
icon="🌯",
descriptor="Protein, veg, and sauce in a tortilla or over rice",
title="Burrito / Taco",
required=[
AssemblyRole("tortilla or wrap", [
@ -183,21 +170,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Fold in the sides and roll tightly. Optionally toast seam-side down 1-2 minutes.",
],
notes="Works as a burrito (rolled), taco (folded), or quesadilla (cheese only, pressed flat).",
role_hints={
"tortilla or wrap": "The foundation -- what holds everything",
"protein": "The main filling",
"rice or starch": "Optional base layer",
"cheese": "Optional -- melts into the filling",
"salsa or sauce": "Optional -- adds moisture and heat",
"sour cream or yogurt": "Optional -- cool contrast to heat",
"vegetables": "Optional -- adds texture and colour",
},
),
AssemblyTemplate(
id=-2,
slug="fried_rice",
icon="🍳",
descriptor="Rice + egg + whatever's in the fridge",
title="Fried Rice",
required=[
AssemblyRole("cooked rice", [
@ -230,21 +205,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Season with soy sauce and any other sauces. Toss to combine.",
],
notes="Add a fried egg on top. A drizzle of sesame oil at the end adds a lot.",
role_hints={
"cooked rice": "Day-old cold rice works best",
"protein": "Pre-cooked or raw -- cook before adding rice",
"soy sauce or seasoning": "The primary flavour driver",
"oil": "High smoke-point oil for high heat",
"egg": "Scrambled in the same pan",
"vegetables": "Add crunch and colour",
"garlic or ginger": "Aromatic base -- add first",
},
),
AssemblyTemplate(
id=-3,
slug="omelette_scramble",
icon="🥚",
descriptor="Eggs with fillings, pan-cooked",
title="Omelette / Scramble",
required=[
AssemblyRole("eggs", ["egg"]),
@ -275,19 +238,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Season and serve immediately.",
],
notes="Works for breakfast, lunch, or a quick dinner. Any leftover vegetables work well.",
role_hints={
"eggs": "The base -- beat with a splash of water",
"cheese": "Fold in just before serving",
"vegetables": "Saute first, then add eggs",
"protein": "Cook through before adding eggs",
"herbs or seasoning": "Season at the end",
},
),
AssemblyTemplate(
id=-4,
slug="stir_fry",
icon="🥢",
descriptor="High-heat protein + veg in sauce",
title="Stir Fry",
required=[
AssemblyRole("vegetables", [
@ -318,20 +271,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Serve over rice or noodles.",
],
notes="High heat is the key. Do not crowd the pan -- cook in batches if needed.",
role_hints={
"vegetables": "Cut to similar size for even cooking",
"starch base": "Serve under or toss with the stir fry",
"protein": "Cook first, remove, add back at end",
"sauce": "Add last -- toss for 1-2 minutes only",
"garlic or ginger": "Add early for aromatic base",
"oil": "High smoke-point oil only",
},
),
AssemblyTemplate(
id=-5,
slug="pasta",
icon="🍝",
descriptor="Pantry pasta with flexible sauce",
title="Pasta with Whatever You Have",
required=[
AssemblyRole("pasta", [
@ -365,20 +307,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Toss cooked pasta with sauce. Finish with cheese if using.",
],
notes="Pasta water is the secret -- the starch thickens and binds any sauce.",
role_hints={
"pasta": "The base -- cook al dente, reserve pasta water",
"sauce base": "Simmer 5 min; pasta water loosens it",
"protein": "Cook through before adding sauce",
"cheese": "Finish off heat to avoid graininess",
"vegetables": "Saute until tender before adding sauce",
"garlic": "Saute in oil first -- the flavour foundation",
},
),
AssemblyTemplate(
id=-6,
slug="sandwich_wrap",
icon="🥪",
descriptor="Protein + veg between bread or in a wrap",
title="Sandwich / Wrap",
required=[
AssemblyRole("bread or wrap", [
@ -410,19 +341,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Press together and cut diagonally.",
],
notes="Leftovers, deli meat, canned fish -- nearly anything works between bread.",
role_hints={
"bread or wrap": "Toast for better texture",
"protein": "Layer on first after condiments",
"cheese": "Goes on top of protein",
"condiment": "Spread on both inner surfaces",
"vegetables": "Top layer -- keeps bread from getting soggy",
},
),
AssemblyTemplate(
id=-7,
slug="grain_bowl",
icon="🥗",
descriptor="Grain base + protein + toppings + dressing",
title="Grain Bowl",
required=[
AssemblyRole("grain base", [
@ -456,19 +377,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Drizzle with dressing and add toppings.",
],
notes="Great for meal prep -- cook grains and proteins in bulk, assemble bowls all week.",
role_hints={
"grain base": "Season while cooking -- bland grains sink the bowl",
"protein": "Slice or shred; arrange on top",
"vegetables": "Roast or saute for best flavour",
"dressing or sauce": "Drizzle last -- ties everything together",
"toppings": "Add crunch and contrast",
},
),
AssemblyTemplate(
id=-8,
slug="soup_stew",
icon="🥣",
descriptor="Liquid-based, flexible ingredients",
title="Soup / Stew",
required=[
# Narrow to dedicated soup bases — tomato sauce and coconut milk are
@ -504,19 +415,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Season to taste and simmer at least 20 minutes for flavors to develop.",
],
notes="Soups and stews improve overnight in the fridge. Almost any combination works.",
role_hints={
"broth or stock": "The liquid base -- determines overall flavour",
"protein": "Brown first for deeper flavour",
"vegetables": "Dense veg first; quick-cooking veg last",
"starch thickener": "Adds body and turns soup into stew",
"seasoning": "Taste and adjust after 20 min simmer",
},
),
AssemblyTemplate(
id=-9,
slug="casserole_bake",
icon="🫙",
descriptor="Oven bake with protein, veg, starch",
title="Casserole / Bake",
required=[
AssemblyRole("starch or base", [
@ -556,20 +457,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Bake covered 25 minutes, then uncovered 15 minutes until golden and bubbly.",
],
notes="Classic pantry dump dinner. Cream of anything soup is the universal binder.",
role_hints={
"starch or base": "Cook slightly underdone -- finishes in oven",
"binder or sauce": "Coats everything and holds the bake together",
"protein": "Pre-cook before mixing in",
"vegetables": "Chop small for even distribution",
"cheese topping": "Goes on last -- browns in the final 15 min",
"seasoning": "Casseroles need more salt than you think",
},
),
AssemblyTemplate(
id=-10,
slug="pancakes_quickbread",
icon="🥞",
descriptor="Batter-based; sweet or savory",
title="Pancakes / Waffles / Quick Bread",
required=[
AssemblyRole("flour or baking mix", [
@ -605,20 +495,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"For muffins or quick bread: pour into greased pan, bake at 375 F until a toothpick comes out clean.",
],
notes="Overmixing develops gluten and makes pancakes tough. Stop when just combined.",
role_hints={
"flour or baking mix": "Whisk dry ingredients together first",
"leavening or egg": "Activates rise -- don't skip",
"liquid": "Add to dry ingredients; lumps are fine",
"fat": "Adds richness and prevents sticking",
"sweetener": "Mix into wet ingredients",
"mix-ins": "Fold in last -- gently",
},
),
AssemblyTemplate(
id=-11,
slug="porridge_oatmeal",
icon="🌾",
descriptor="Oat or grain base with toppings",
title="Porridge / Oatmeal",
required=[
AssemblyRole("oats or grain porridge", [
@ -641,20 +520,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Top with fruit, nuts, or seeds and serve immediately.",
],
notes="Overnight oats: skip cooking — soak oats in cold milk overnight in the fridge.",
role_hints={
"oats or grain porridge": "1 part oats to 2 parts liquid",
"liquid": "Use milk for creamier result",
"sweetener": "Stir in after cooking",
"fruit": "Add fresh on top or simmer dried fruit in",
"toppings": "Add last for crunch",
"spice": "Stir in with sweetener",
},
),
AssemblyTemplate(
id=-12,
slug="pie_pot_pie",
icon="🥧",
descriptor="Pastry or biscuit crust with filling",
title="Pie / Pot Pie",
required=[
AssemblyRole("pastry or crust", [
@ -693,20 +561,9 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"For sweet pie: fill unbaked crust with fruit filling, top with second crust or crumble, bake similarly.",
],
notes="Puff pastry from the freezer is the shortcut to impressive pot pies. Thaw in the fridge overnight.",
role_hints={
"pastry or crust": "Thaw puff pastry overnight in fridge",
"protein filling": "Cook through before adding to filling",
"vegetables": "Chop small; cook until just tender",
"sauce or binder": "Holds the filling together in the crust",
"seasoning": "Fillings need generous seasoning",
"sweet filling": "For dessert pies -- fruit + sugar",
},
),
AssemblyTemplate(
id=-13,
slug="pudding_custard",
icon="🍮",
descriptor="Dairy-based set dessert",
title="Pudding / Custard",
required=[
AssemblyRole("dairy or dairy-free milk", [
@ -744,58 +601,10 @@ ASSEMBLY_TEMPLATES: list[AssemblyTemplate] = [
"Pour into dishes and refrigerate at least 2 hours to set.",
],
notes="UK-style pudding is broad — bread pudding, rice pudding, spotted dick, treacle sponge all count.",
role_hints={
"dairy or dairy-free milk": "Heat until steaming before adding to eggs",
"thickener or set": "Cornstarch for stovetop; eggs for baked custard",
"sweetener or flavouring": "Signals dessert intent -- required",
"sweetener": "Adjust to taste",
"flavouring": "Add off-heat to preserve aroma",
"starchy base": "For bread pudding or rice pudding",
"fruit": "Layer in or fold through before setting",
},
),
]
# Slug to template lookup (built once at import time)
_TEMPLATE_BY_SLUG: dict[str, AssemblyTemplate] = {
t.slug: t for t in ASSEMBLY_TEMPLATES
}
def get_templates_for_api() -> list[dict]:
"""Serialise all 13 templates for GET /api/recipes/templates.
Combines required and optional roles into a single ordered role_sequence
with required roles first.
"""
out = []
for tmpl in ASSEMBLY_TEMPLATES:
roles = []
for role in tmpl.required:
roles.append({
"display": role.display,
"required": True,
"keywords": role.keywords,
"hint": tmpl.role_hints.get(role.display, ""),
})
for role in tmpl.optional:
roles.append({
"display": role.display,
"required": False,
"keywords": role.keywords,
"hint": tmpl.role_hints.get(role.display, ""),
})
out.append({
"id": tmpl.slug,
"title": tmpl.title,
"icon": tmpl.icon,
"descriptor": tmpl.descriptor,
"role_sequence": roles,
})
return out
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
@ -870,148 +679,3 @@ def match_assembly_templates(
# Sort by optional coverage descending — best-matched templates first
results.sort(key=lambda s: s.match_count, reverse=True)
return results
def get_role_candidates(
template_slug: str,
role_display: str,
pantry_set: set[str],
prior_picks: list[str],
profile_index: dict[str, list[str]],
) -> dict:
"""Return ingredient candidates for one wizard step.
Splits candidates into 'compatible' (element overlap with prior picks)
and 'other' (valid for role but no overlap).
profile_index: {ingredient_name: [element_tag, ...]} -- pre-loaded from
Store.get_element_profiles() by the caller so this function stays DB-free.
Returns {"compatible": [...], "other": [...], "available_tags": [...]}
where each item is {"name": str, "in_pantry": bool, "tags": [str]}.
"""
tmpl = _TEMPLATE_BY_SLUG.get(template_slug)
if tmpl is None:
return {"compatible": [], "other": [], "available_tags": []}
# Find the AssemblyRole for this display name
target_role: AssemblyRole | None = None
for role in tmpl.required + tmpl.optional:
if role.display == role_display:
target_role = role
break
if target_role is None:
return {"compatible": [], "other": [], "available_tags": []}
# Build prior-pick element set for compatibility scoring
prior_elements: set[str] = set()
for pick in prior_picks:
prior_elements.update(profile_index.get(pick, []))
# Find pantry items that match this role
pantry_matches = _matches_role(target_role, pantry_set)
# Build keyword-based "other" candidates from role keywords not in pantry
pantry_lower = {p.lower() for p in pantry_set}
other_names: list[str] = []
for kw in target_role.keywords:
if not any(kw in item.lower() for item in pantry_lower):
if len(kw) >= 4:
other_names.append(kw.title())
def _make_item(name: str, in_pantry: bool) -> dict:
tags = profile_index.get(name, profile_index.get(name.lower(), []))
return {"name": name, "in_pantry": in_pantry, "tags": tags}
# Score: compatible if shares any element with prior picks (or no prior picks yet)
compatible: list[dict] = []
other: list[dict] = []
for name in pantry_matches:
item_elements = set(profile_index.get(name, []))
item = _make_item(name, in_pantry=True)
if not prior_elements or item_elements & prior_elements:
compatible.append(item)
else:
other.append(item)
for name in other_names:
other.append(_make_item(name, in_pantry=False))
# available_tags: union of all tags in the full candidate set
all_tags: set[str] = set()
for item in compatible + other:
all_tags.update(item["tags"])
return {
"compatible": compatible,
"other": other,
"available_tags": sorted(all_tags),
}
def build_from_selection(
template_slug: str,
role_overrides: dict[str, str],
pantry_set: set[str],
) -> "RecipeSuggestion | None":
"""Build a RecipeSuggestion from explicit role selections.
role_overrides: {role.display -> chosen pantry item name}
Returns None if template not found or any required role is uncovered.
"""
tmpl = _TEMPLATE_BY_SLUG.get(template_slug)
if tmpl is None:
return None
seed = _pantry_hash(pantry_set)
# Validate required roles: covered by override OR pantry match
matched_required: list[str] = []
for role in tmpl.required:
chosen = role_overrides.get(role.display)
if chosen:
matched_required.append(chosen)
else:
hits = _matches_role(role, pantry_set)
if not hits:
return None
matched_required.append(_pick_one(hits, seed + tmpl.id))
# Collect optional matches (override preferred, then pantry match)
matched_optional: list[str] = []
for role in tmpl.optional:
chosen = role_overrides.get(role.display)
if chosen:
matched_optional.append(chosen)
else:
hits = _matches_role(role, pantry_set)
if hits:
matched_optional.append(_pick_one(hits, seed + tmpl.id))
all_matched = matched_required + matched_optional
# Build title: prefer override items for personalisation
effective_pantry = pantry_set | set(role_overrides.values())
title = _personalized_title(tmpl, effective_pantry, seed + tmpl.id)
# Items in role_overrides that aren't in the user's pantry = shopping list
missing = [
item for item in role_overrides.values()
if item and item not in pantry_set
]
return RecipeSuggestion(
id=tmpl.id,
title=title,
match_count=len(all_matched),
element_coverage={},
swap_candidates=[],
matched_ingredients=all_matched,
missing_ingredients=missing,
directions=tmpl.directions,
notes=tmpl.notes,
level=1,
is_wildcard=False,
nutrition=None,
)

View file

@ -1,256 +0,0 @@
"""
Browse counts cache pre-computes and persists recipe counts for all
browse domain keyword sets so category/subcategory page loads never
hit the 3.8 GB FTS index at request time.
Counts change only when the corpus changes (after a pipeline run).
The cache is a small SQLite file separate from both the read-only
corpus DB and per-user kiwi.db files, so the container can write it.
Refresh triggers:
1. Startup if cache is missing or older than STALE_DAYS
2. Nightly asyncio background task started in main.py lifespan
3. Pipeline infer_recipe_tags.py calls refresh() at end of run
The in-memory _COUNT_CACHE in store.py is pre-warmed from this file
on startup, so FTS queries are never needed for known keyword sets.
"""
from __future__ import annotations
import logging
import sqlite3
from datetime import datetime, timezone
from pathlib import Path
logger = logging.getLogger(__name__)
STALE_DAYS = 7
# ---------------------------------------------------------------------------
# Internal helpers
# ---------------------------------------------------------------------------
def _kw_key(keywords: list[str]) -> str:
"""Stable string key for a keyword list — sorted and pipe-joined."""
return "|".join(sorted(keywords))
def _fts_match_expr(keywords: list[str]) -> str:
phrases = ['"' + kw.replace('"', '""') + '"' for kw in keywords]
return " OR ".join(phrases)
def _ensure_schema(conn: sqlite3.Connection) -> None:
conn.execute("""
CREATE TABLE IF NOT EXISTS browse_counts (
keywords_key TEXT PRIMARY KEY,
count INTEGER NOT NULL,
computed_at TEXT NOT NULL
)
""")
conn.execute("""
CREATE TABLE IF NOT EXISTS browse_counts_meta (
key TEXT PRIMARY KEY,
value TEXT NOT NULL
)
""")
conn.commit()
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def is_stale(cache_path: Path, max_age_days: int = STALE_DAYS) -> bool:
"""Return True if the cache is missing, empty, or older than max_age_days."""
if not cache_path.exists():
return True
try:
conn = sqlite3.connect(cache_path)
row = conn.execute(
"SELECT value FROM browse_counts_meta WHERE key = 'refreshed_at'"
).fetchone()
conn.close()
if row is None:
return True
age = (datetime.now(timezone.utc) - datetime.fromisoformat(row[0])).days
return age >= max_age_days
except Exception:
return True
def load_into_memory(cache_path: Path, count_cache: dict, corpus_path: str) -> int:
"""
Load all rows from the cache file into the in-memory count_cache dict.
Uses corpus_path (the current RECIPE_DB_PATH env value) as the cache key,
not what was stored in the file the file may have been built against a
different mount path (e.g. pipeline ran on host, container sees a different
path). Counts are corpus-content-derived and path-independent.
Returns the number of entries loaded.
"""
if not cache_path.exists():
return 0
try:
conn = sqlite3.connect(cache_path)
rows = conn.execute("SELECT keywords_key, count FROM browse_counts").fetchall()
conn.close()
loaded = 0
for kw_key, count in rows:
keywords = kw_key.split("|") if kw_key else []
cache_key = (corpus_path, *sorted(keywords))
count_cache[cache_key] = count
loaded += 1
logger.info("browse_counts: warmed %d entries from %s", loaded, cache_path)
return loaded
except Exception as exc:
logger.warning("browse_counts: load failed: %s", exc)
return 0
def refresh(corpus_path: str, cache_path: Path) -> int:
"""
Run FTS5 queries for every keyword set in browser_domains.DOMAINS
and write results to cache_path.
Safe to call from both the host pipeline script and the in-container
nightly task. The corpus_path must be reachable and readable from
the calling process.
Returns the number of keyword sets computed.
"""
from app.services.recipe.browser_domains import DOMAINS # local import — avoid circular
cache_path.parent.mkdir(parents=True, exist_ok=True)
cache_conn = sqlite3.connect(cache_path)
_ensure_schema(cache_conn)
# Collect every unique keyword list across all domains/categories/subcategories.
# DOMAINS structure: {domain: {label: str, categories: {cat_name: {keywords, subcategories}}}}
seen: dict[str, list[str]] = {}
for domain_data in DOMAINS.values():
for cat_data in domain_data.get("categories", {}).values():
if not isinstance(cat_data, dict):
continue
top_kws = cat_data.get("keywords", [])
if top_kws:
seen[_kw_key(top_kws)] = top_kws
for subcat_kws in cat_data.get("subcategories", {}).values():
if subcat_kws:
seen[_kw_key(subcat_kws)] = subcat_kws
try:
corpus_conn = sqlite3.connect(f"file:{corpus_path}?mode=ro", uri=True)
except Exception as exc:
logger.error("browse_counts: cannot open corpus %s: %s", corpus_path, exc)
cache_conn.close()
return 0
now = datetime.now(timezone.utc).isoformat()
computed = 0
try:
for kw_key, kws in seen.items():
try:
row = corpus_conn.execute(
"SELECT count(*) FROM recipe_browser_fts WHERE recipe_browser_fts MATCH ?",
(_fts_match_expr(kws),),
).fetchone()
count = row[0] if row else 0
cache_conn.execute(
"INSERT OR REPLACE INTO browse_counts (keywords_key, count, computed_at)"
" VALUES (?, ?, ?)",
(kw_key, count, now),
)
computed += 1
except Exception as exc:
logger.warning("browse_counts: query failed key=%r: %s", kw_key[:60], exc)
# Merge accepted community tags into counts.
# For each (domain, category, subcategory) that has accepted community
# tags, add the count of distinct tagged recipe_ids to the FTS count.
# The two overlap rarely (community tags exist precisely because FTS
# missed those recipes), so simple addition is accurate enough.
try:
_merge_community_tag_counts(cache_conn, DOMAINS, now)
except Exception as exc:
logger.warning("browse_counts: community merge skipped: %s", exc)
cache_conn.execute(
"INSERT OR REPLACE INTO browse_counts_meta (key, value) VALUES ('refreshed_at', ?)",
(now,),
)
cache_conn.execute(
"INSERT OR REPLACE INTO browse_counts_meta (key, value) VALUES ('corpus_path', ?)",
(corpus_path,),
)
cache_conn.commit()
logger.info("browse_counts: wrote %d counts → %s", computed, cache_path)
finally:
corpus_conn.close()
cache_conn.close()
return computed
def _merge_community_tag_counts(
cache_conn: sqlite3.Connection,
domains: dict,
now: str,
threshold: int = 2,
) -> None:
"""Add accepted community tag counts on top of FTS counts in the cache.
Queries the community PostgreSQL store (if available) for accepted tags
grouped by (domain, category, subcategory), maps each back to its keyword
set key, then increments the cached count.
Silently skips if community features are unavailable.
"""
try:
from app.api.endpoints.community import _get_community_store
store = _get_community_store()
if store is None:
return
except Exception:
return
for domain_id, domain_data in domains.items():
for cat_name, cat_data in domain_data.get("categories", {}).items():
if not isinstance(cat_data, dict):
continue
# Check subcategories
for subcat_name, subcat_kws in cat_data.get("subcategories", {}).items():
if not subcat_kws:
continue
ids = store.get_accepted_recipe_ids_for_subcategory(
domain=domain_id,
category=cat_name,
subcategory=subcat_name,
threshold=threshold,
)
if not ids:
continue
kw_key = _kw_key(subcat_kws)
cache_conn.execute(
"UPDATE browse_counts SET count = count + ? WHERE keywords_key = ?",
(len(ids), kw_key),
)
# Check category-level tags (subcategory IS NULL)
top_kws = cat_data.get("keywords", [])
if top_kws:
ids = store.get_accepted_recipe_ids_for_subcategory(
domain=domain_id,
category=cat_name,
subcategory=None,
threshold=threshold,
)
if ids:
kw_key = _kw_key(top_kws)
cache_conn.execute(
"UPDATE browse_counts SET count = count + ? WHERE keywords_key = ?",
(len(ids), kw_key),
)
logger.info("browse_counts: community tag counts merged")

View file

@ -5,12 +5,6 @@ Each domain provides a two-level category hierarchy for browsing the recipe corp
Keyword matching is case-insensitive against the recipes.category column and the
recipes.keywords JSON array. A recipe may appear in multiple categories (correct).
Category values are either:
- list[str] flat keyword list (no subcategories)
- dict {"keywords": list[str], "subcategories": {name: list[str]}}
keywords covers the whole category (used for "All X" browse);
subcategories each have their own narrower keyword list.
These are starter mappings based on the food.com dataset structure. Run:
SELECT category, count(*) FROM recipes
@ -25,479 +19,26 @@ DOMAINS: dict[str, dict] = {
"cuisine": {
"label": "Cuisine",
"categories": {
"Italian": {
"keywords": ["italian", "pasta", "pizza", "risotto", "lasagna", "carbonara"],
"subcategories": {
"Sicilian": ["sicilian", "sicily", "arancini", "caponata",
"involtini", "cannoli"],
"Neapolitan": ["neapolitan", "naples", "pizza napoletana",
"sfogliatelle", "ragù"],
"Tuscan": ["tuscan", "tuscany", "ribollita", "bistecca",
"pappardelle", "crostini"],
"Roman": ["roman", "rome", "cacio e pepe", "carbonara",
"amatriciana", "gricia", "supplì"],
"Venetian": ["venetian", "venice", "risotto", "bigoli",
"baccalà", "sarde in saor"],
"Ligurian": ["ligurian", "liguria", "pesto", "focaccia",
"trofie", "farinata"],
},
},
"Mexican": {
"keywords": ["mexican", "taco", "enchilada", "burrito", "salsa",
"guacamole", "mole", "tamale"],
"subcategories": {
"Oaxacan": ["oaxacan", "oaxaca", "mole negro", "tlayuda",
"chapulines", "mezcal", "tasajo", "memelas"],
"Yucatecan": ["yucatecan", "yucatan", "cochinita pibil", "poc chuc",
"sopa de lima", "panuchos", "papadzules"],
"Veracruz": ["veracruz", "veracruzana", "huachinango",
"picadas", "enfrijoladas", "caldo de mariscos"],
"Street Food": ["taco", "elote", "tlacoyos", "torta", "tamale",
"quesadilla", "tostada", "sope", "gordita"],
"Mole": ["mole", "mole negro", "mole rojo", "mole verde",
"mole poblano", "mole amarillo", "pipián"],
"Baja / Cal-Mex": ["baja", "baja california", "cal-mex", "baja fish taco",
"fish taco", "carne asada fries", "california burrito",
"birria", "birria tacos", "quesabirria",
"lobster puerto nuevo", "tijuana", "ensenada",
"agua fresca", "caesar salad tijuana"],
"Mexico City": ["mexico city", "chilaquiles", "tlayuda cdmx",
"tacos de canasta", "torta ahogada", "pozole",
"chiles en nogada"],
},
},
"Asian": {
"keywords": ["asian", "chinese", "japanese", "thai", "korean", "vietnamese",
"stir fry", "stir-fry", "ramen", "sushi", "malaysian",
"taiwanese", "singaporean", "burmese", "cambodian",
"laotian", "mongolian", "hong kong"],
"subcategories": {
"Korean": ["korean", "kimchi", "bibimbap", "bulgogi", "japchae",
"doenjang", "gochujang", "tteokbokki", "sundubu",
"galbi", "jjigae", "kbbq", "korean fried chicken"],
"Japanese": ["japanese", "sushi", "ramen", "tempura", "miso",
"teriyaki", "udon", "soba", "bento", "yakitori",
"tonkatsu", "onigiri", "okonomiyaki", "takoyaki",
"kaiseki", "izakaya"],
"Chinese": ["chinese", "dim sum", "fried rice", "dumplings", "wonton",
"spring roll", "szechuan", "sichuan", "cantonese",
"chow mein", "mapo tofu", "lo mein", "hot pot",
"peking duck", "char siu", "congee"],
"Thai": ["thai", "pad thai", "green curry", "red curry",
"coconut milk", "lemongrass", "satay", "tom yum",
"larb", "khao man gai", "massaman", "pad see ew"],
"Vietnamese": ["vietnamese", "pho", "banh mi", "spring rolls",
"vermicelli", "nuoc cham", "bun bo hue",
"banh xeo", "com tam", "bun cha"],
"Filipino": ["filipino", "adobo", "sinigang", "pancit", "lumpia",
"kare-kare", "lechon", "sisig", "halo-halo",
"dinuguan", "tinola", "bistek"],
"Indonesian": ["indonesian", "rendang", "nasi goreng", "gado-gado",
"tempeh", "sambal", "soto", "opor ayam",
"bakso", "mie goreng", "nasi uduk"],
"Malaysian": ["malaysian", "laksa", "nasi lemak", "char kway teow",
"satay malaysia", "roti canai", "bak kut teh",
"cendol", "mee goreng mamak", "curry laksa"],
"Taiwanese": ["taiwanese", "beef noodle soup", "lu rou fan",
"oyster vermicelli", "scallion pancake taiwan",
"pork chop rice", "three cup chicken",
"bubble tea", "stinky tofu", "ba wan"],
"Singaporean": ["singaporean", "chicken rice", "chili crab",
"singaporean laksa", "bak chor mee", "rojak",
"kaya toast", "nasi padang", "satay singapore"],
"Burmese": ["burmese", "myanmar", "mohinga", "laphet thoke",
"tea leaf salad", "ohn no khao swe",
"mont di", "nangyi thoke"],
"Hong Kong": ["hong kong", "hk style", "pineapple bun",
"wonton noodle soup", "hk milk tea", "egg tart",
"typhoon shelter crab", "char siu bao", "jook",
"congee hk", "silk stocking tea", "dan tat",
"siu mai hk", "cheung fun"],
"Cambodian": ["cambodian", "khmer", "amok", "lok lak",
"kuy teav", "bai sach chrouk", "nom banh chok",
"samlor korko", "beef loc lac"],
"Laotian": ["laotian", "lao", "larb", "tam mak hoong",
"or lam", "khao niaw", "ping kai",
"naem khao", "khao piak sen", "mok pa"],
"Mongolian": ["mongolian", "buuz", "khuushuur", "tsuivan",
"boodog", "airag", "khorkhog", "bansh",
"guriltai shol", "suutei tsai"],
"South Asian Fusion": ["south asian fusion", "indo-chinese",
"hakka chinese", "chilli chicken",
"manchurian", "schezwan"],
},
},
"Indian": {
"keywords": ["indian", "curry", "lentil", "dal", "tikka", "masala",
"biryani", "naan", "chutney", "pakistani", "sri lankan",
"bangladeshi", "nepali"],
"subcategories": {
"North Indian": ["north indian", "punjabi", "mughal", "tikka masala",
"naan", "tandoori", "butter chicken", "palak paneer",
"chole", "rajma", "aloo gobi"],
"South Indian": ["south indian", "tamil", "kerala", "dosa", "idli",
"sambar", "rasam", "coconut chutney", "appam",
"fish curry kerala", "puttu", "payasam"],
"Bengali": ["bengali", "mustard fish", "hilsa", "shorshe ilish",
"mishti doi", "rasgulla", "kosha mangsho"],
"Gujarati": ["gujarati", "dhokla", "thepla", "undhiyu",
"khandvi", "fafda", "gujarati dal"],
"Pakistani": ["pakistani", "nihari", "haleem", "seekh kebab",
"karahi", "biryani karachi", "chapli kebab",
"halwa puri", "paya"],
"Sri Lankan": ["sri lankan", "kottu roti", "hoppers", "pol sambol",
"sri lankan curry", "lamprais", "string hoppers",
"wambatu moju"],
"Bangladeshi": ["bangladeshi", "bangladesh", "dhaka biryani",
"shutki", "pitha", "hilsa curry", "kacchi biryani",
"bhuna khichuri", "doi maach", "rezala"],
"Nepali": ["nepali", "dal bhat", "momos", "sekuwa",
"sel roti", "gundruk", "thukpa"],
},
},
"Mediterranean": {
"keywords": ["mediterranean", "greek", "middle eastern", "turkish",
"lebanese", "jewish", "palestinian", "yemeni", "egyptian",
"syrian", "iraqi", "jordanian"],
"subcategories": {
"Greek": ["greek", "feta", "tzatziki", "moussaka", "spanakopita",
"souvlaki", "dolmades", "spanakopita", "tiropita",
"galaktoboureko"],
"Turkish": ["turkish", "kebab", "borek", "meze", "baklava",
"lahmacun", "menemen", "pide", "iskender",
"kisir", "simit"],
"Syrian": ["syrian", "fattet hummus", "kibbeh syria",
"muhammara", "maklouba syria", "sfeeha",
"halawet el jibn"],
"Lebanese": ["lebanese", "middle eastern", "hummus", "falafel",
"tabbouleh", "kibbeh", "fattoush", "manakish",
"kafta", "sfiha"],
"Jewish": ["jewish", "israeli", "ashkenazi", "sephardic",
"shakshuka", "sabich", "za'atar", "tahini",
"zhug", "zhoug", "s'khug", "z'houg",
"hawaiij", "hawaij", "hawayej",
"matzo", "latke", "rugelach", "babka", "challah",
"cholent", "gefilte fish", "brisket", "kugel",
"new york jewish", "new york deli", "pastrami",
"knish", "lox", "bagel and lox", "jewish deli"],
"Palestinian": ["palestinian", "musakhan", "maqluba", "knafeh",
"maftoul", "freekeh", "sumac chicken"],
"Yemeni": ["yemeni", "saltah", "lahoh", "bint al-sahn",
"zhug", "zhoug", "hulba", "fahsa",
"hawaiij", "hawaij", "hawayej"],
"Egyptian": ["egyptian", "koshari", "molokhia", "mahshi",
"ful medames", "ta'ameya", "feteer meshaltet"],
},
},
"American": {
"keywords": ["american", "southern", "comfort food", "cajun", "creole",
"hawaiian", "tex-mex", "soul food"],
"subcategories": {
"Southern": ["southern", "soul food", "fried chicken",
"collard greens", "cornbread", "biscuits and gravy",
"mac and cheese", "sweet potato pie", "okra"],
"Cajun/Creole": ["cajun", "creole", "new orleans", "gumbo",
"jambalaya", "etouffee", "dirty rice", "po'boy",
"muffuletta", "red beans and rice"],
"Tex-Mex": ["tex-mex", "southwestern", "chili", "fajita",
"queso", "breakfast taco", "chile con carne"],
"New England": ["new england", "chowder", "lobster", "clam",
"maple", "yankee", "boston baked beans",
"johnnycake", "fish and chips"],
"Pacific Northwest": ["pacific northwest", "pnw", "dungeness crab",
"salmon", "cedar plank", "razor clam",
"geoduck", "chanterelle", "marionberry"],
"Hawaiian": ["hawaiian", "hawaii", "plate lunch", "loco moco",
"poke", "spam musubi", "kalua pig", "lau lau",
"haupia", "poi", "manapua", "garlic shrimp",
"saimin", "huli huli", "malasada"],
},
},
"BBQ & Smoke": {
# Top-level keywords use broad corpus-friendly terms that appear in
# food.com keyword/category fields (e.g. "BBQ", "Oven BBQ", "Smoker").
# Subcategory keywords remain specific for drill-down filtering.
"keywords": ["bbq", "barbecue", "barbeque", "smoked", "smoky",
"smoke", "pit", "smoke ring", "low and slow",
"brisket", "pulled pork", "ribs", "spare ribs",
"baby back", "baby back ribs", "dry rub", "wet rub",
"cookout", "smoker", "smoked meat", "smoked chicken",
"smoked pork", "smoked beef", "smoked turkey",
"pit smoked", "wood smoked", "slow smoked",
"charcoal", "chargrilled", "burnt ends"],
"subcategories": {
"Texas BBQ": ["texas bbq", "central texas bbq", "brisket",
"beef brisket", "beef ribs", "smoked brisket",
"post oak", "salt and pepper rub",
"east texas bbq", "lockhart", "franklin style"],
"Carolina BBQ": ["carolina bbq", "north carolina bbq", "whole hog",
"vinegar sauce", "vinegar bbq", "lexington style",
"eastern nc", "south carolina bbq", "mustard sauce",
"carolina pulled pork"],
"Kansas City BBQ": ["kansas city bbq", "kc bbq", "burnt ends",
"sweet bbq sauce", "tomato molasses sauce",
"baby back ribs", "kansas city ribs"],
"Memphis BBQ": ["memphis bbq", "dry rub ribs", "wet ribs",
"memphis style", "dry rub pork", "memphis ribs"],
"Alabama BBQ": ["alabama bbq", "white sauce", "alabama white sauce",
"smoked chicken", "white bbq sauce"],
"Kentucky BBQ": ["kentucky bbq", "mutton bbq", "owensboro bbq",
"black dip", "western kentucky barbecue", "mutton"],
"St. Louis BBQ": ["st louis bbq", "st louis ribs", "st. louis ribs",
"st louis cut ribs", "spare ribs st louis"],
"Backyard Grill": ["backyard bbq", "cookout", "grilled burgers",
"charcoal grill", "kettle grill", "tailgate",
"grill out", "backyard grilling"],
},
},
"European": {
"keywords": ["french", "german", "spanish", "british", "irish", "scottish",
"welsh", "scandinavian", "nordic", "eastern european"],
"subcategories": {
"French": ["french", "provencal", "beurre", "crepe",
"ratatouille", "cassoulet", "bouillabaisse"],
"Spanish": ["spanish", "paella", "tapas", "gazpacho",
"tortilla espanola", "chorizo"],
"German": ["german", "bratwurst", "sauerkraut", "schnitzel",
"pretzel", "strudel"],
"British": ["british", "english", "pub food", "cornish",
"shepherd's pie", "bangers", "toad in the hole",
"coronation chicken", "london", "londoner",
"cornish pasty", "ploughman's"],
"Irish": ["irish", "ireland", "colcannon", "coddle",
"irish stew", "soda bread", "boxty", "champ"],
"Scottish": ["scottish", "scotland", "haggis", "cullen skink",
"cranachan", "scotch broth", "glaswegian",
"neeps and tatties", "tablet"],
"Scandinavian": ["scandinavian", "nordic", "swedish", "norwegian",
"danish", "finnish", "gravlax", "swedish meatballs",
"lefse", "smörgåsbord", "fika", "crispbread",
"cardamom bun", "herring", "æbleskiver",
"lingonberry", "lutefisk", "janssons frestelse",
"knäckebröd", "kladdkaka"],
"Eastern European": ["eastern european", "polish", "russian", "ukrainian",
"czech", "hungarian", "pierogi", "borscht",
"goulash", "kielbasa", "varenyky", "pelmeni"],
},
},
"Latin American": {
"keywords": ["latin american", "peruvian", "argentinian", "colombian",
"cuban", "caribbean", "brazilian", "venezuelan", "chilean"],
"subcategories": {
"Peruvian": ["peruvian", "ceviche", "lomo saltado", "anticucho",
"aji amarillo", "causa", "leche de tigre",
"arroz con leche peru", "pollo a la brasa"],
"Brazilian": ["brazilian", "churrasco", "feijoada", "pao de queijo",
"brigadeiro", "coxinha", "moqueca", "vatapa",
"caipirinha", "acai bowl"],
"Colombian": ["colombian", "bandeja paisa", "arepas", "empanadas",
"sancocho", "ajiaco", "buñuelos", "changua"],
"Argentinian": ["argentinian", "asado", "chimichurri", "empanadas argentina",
"milanesa", "locro", "dulce de leche", "medialunas"],
"Venezuelan": ["venezuelan", "pabellón criollo", "arepas venezuela",
"hallacas", "cachapas", "tequeños", "caraotas"],
"Chilean": ["chilean", "cazuela", "pastel de choclo", "curanto",
"sopaipillas", "charquicán", "completo"],
"Cuban": ["cuban", "ropa vieja", "moros y cristianos",
"picadillo", "lechon cubano", "vaca frita",
"tostones", "platanos maduros"],
"Jamaican": ["jamaican", "jerk chicken", "jerk pork", "ackee saltfish",
"curry goat", "rice and peas", "escovitch",
"jamaican patty", "callaloo jamaica", "festival"],
"Puerto Rican": ["puerto rican", "mofongo", "pernil", "arroz con gandules",
"sofrito", "pasteles", "tostones pr", "tembleque",
"coquito", "asopao"],
"Dominican": ["dominican", "mangu", "sancocho dominicano",
"pollo guisado", "habichuelas guisadas",
"tostones dominicanos", "morir soñando"],
"Haitian": ["haitian", "griot", "pikliz", "riz et pois",
"joumou", "akra", "pain patate", "labouyi"],
"Trinidad": ["trinidadian", "doubles", "roti trinidad", "pelau",
"callaloo trinidad", "bake and shark",
"curry duck", "oil down"],
},
},
"Central American": {
"keywords": ["central american", "salvadoran", "guatemalan",
"honduran", "nicaraguan", "costa rican", "panamanian"],
"subcategories": {
"Salvadoran": ["salvadoran", "el salvador", "pupusas", "curtido",
"sopa de pata", "nuégados", "atol shuco"],
"Guatemalan": ["guatemalan", "pepián", "jocon", "kak'ik",
"hilachas", "rellenitos", "fiambre"],
"Costa Rican": ["costa rican", "gallo pinto", "casado",
"olla de carne", "arroz con leche cr",
"tres leches cr"],
"Honduran": ["honduran", "baleadas", "sopa de caracol",
"tapado", "machuca", "catrachitas"],
"Nicaraguan": ["nicaraguan", "nacatamal", "vigorón", "indio viejo",
"gallo pinto nicaragua", "güirilas"],
},
},
"African": {
"keywords": ["african", "west african", "east african", "ethiopian",
"nigerian", "ghanaian", "kenyan", "south african",
"senegalese", "tunisian"],
"subcategories": {
"West African": ["west african", "nigerian", "ghanaian",
"jollof rice", "egusi soup", "fufu", "suya",
"groundnut stew", "kelewele", "kontomire",
"waakye", "ofam", "bitterleaf soup"],
"Senegalese": ["senegalese", "senegal", "thieboudienne",
"yassa", "mafe", "thiou", "ceebu jen",
"domoda"],
"Ethiopian & Eritrean": ["ethiopian", "eritrean", "injera", "doro wat",
"kitfo", "tibs", "shiro", "misir wat",
"gomen", "ful ethiopian", "tegamino"],
"East African": ["east african", "kenyan", "tanzanian", "ugandan",
"nyama choma", "ugali", "sukuma wiki",
"pilau kenya", "mandazi", "matoke",
"githeri", "irio"],
"North African": ["north african", "tunisian", "algerian", "libyan",
"brik", "lablabi", "merguez", "shakshuka tunisian",
"harissa tunisian", "couscous algerian"],
"South African": ["south african", "braai", "bobotie", "boerewors",
"bunny chow", "pap", "chakalaka", "biltong",
"malva pudding", "koeksister", "potjiekos"],
"Moroccan": ["moroccan", "tagine", "couscous morocco",
"harissa", "chermoula", "preserved lemon",
"pastilla", "mechoui", "bastilla"],
},
},
"Pacific & Oceania": {
"keywords": ["pacific", "oceania", "polynesian", "melanesian",
"micronesian", "maori", "fijian", "samoan", "tongan",
"hawaiian", "australian", "new zealand"],
"subcategories": {
"Māori / New Zealand": ["maori", "new zealand", "hangi", "rewena bread",
"boil-up", "paua", "kumara", "pavlova nz",
"whitebait fritter", "kina", "hokey pokey"],
"Australian": ["australian", "meat pie", "lamington",
"anzac biscuits", "damper", "barramundi",
"vegemite", "pavlova australia", "tim tam",
"sausage sizzle", "chiko roll", "fairy bread"],
"Fijian": ["fijian", "fiji", "kokoda", "lovo",
"rourou", "palusami fiji", "duruka",
"vakalolo"],
"Samoan": ["samoan", "samoa", "palusami", "oka",
"fa'ausi", "chop suey samoa", "sapasui",
"koko alaisa", "supo esi"],
"Tongan": ["tongan", "tonga", "lu pulu", "'ota 'ika",
"fekkai", "faikakai topai", "kapisi pulu"],
"Papua New Guinean": ["papua new guinea", "png", "mumu",
"sago", "aibika", "kaukau",
"taro png", "coconut crab"],
"Hawaiian": ["hawaiian", "hawaii", "poke", "loco moco",
"plate lunch", "kalua pig", "haupia",
"spam musubi", "poi", "malasada"],
},
},
"Central Asian & Caucasus": {
"keywords": ["central asian", "caucasus", "georgian", "armenian", "uzbek",
"afghan", "persian", "iranian", "azerbaijani", "kazakh"],
"subcategories": {
"Persian / Iranian": ["persian", "iranian", "ghormeh sabzi", "fesenjan",
"tahdig", "joojeh kabab", "ash reshteh",
"zereshk polo", "khoresh", "mast o khiar",
"kashk-e-bademjan", "mirza ghasemi",
"baghali polo"],
"Georgian": ["georgian", "georgia", "khachapuri", "khinkali",
"churchkhela", "ajapsandali", "satsivi",
"pkhali", "lobiani", "badrijani nigvzit"],
"Armenian": ["armenian", "dolma armenia", "lahmajoun",
"manti armenia", "ghapama", "basturma",
"harissa armenia", "nazook", "tolma"],
"Azerbaijani": ["azerbaijani", "azerbaijan", "plov azerbaijan",
"dolma azeri", "dushbara", "levengi",
"shah plov", "gutab"],
"Uzbek": ["uzbek", "uzbekistan", "plov", "samsa",
"lagman", "shashlik", "manti uzbek",
"non bread", "dimlama", "sumalak"],
"Afghan": ["afghan", "afghanistan", "kabuli pulao", "mantu",
"bolani", "qorma", "ashak", "shorwa",
"aushak", "borani banjan"],
"Kazakh": ["kazakh", "beshbarmak", "kuyrdak", "baursak",
"kurt", "shubat", "kazy"],
},
},
"Italian": ["italian", "pasta", "pizza", "risotto", "lasagna", "carbonara"],
"Mexican": ["mexican", "tex-mex", "taco", "enchilada", "burrito", "salsa", "guacamole"],
"Asian": ["asian", "chinese", "japanese", "thai", "korean", "vietnamese", "stir fry", "stir-fry", "ramen", "sushi"],
"American": ["american", "southern", "bbq", "barbecue", "comfort food", "cajun", "creole"],
"Mediterranean": ["mediterranean", "greek", "middle eastern", "turkish", "moroccan", "lebanese"],
"Indian": ["indian", "curry", "lentil", "dal", "tikka", "masala", "biryani"],
"European": ["french", "german", "spanish", "british", "irish", "scandinavian"],
"Latin American": ["latin american", "peruvian", "argentinian", "colombian", "cuban", "caribbean"],
},
},
"meal_type": {
"label": "Meal Type",
"categories": {
"Breakfast": {
"keywords": ["breakfast", "brunch", "eggs", "pancakes", "waffles",
"oatmeal", "muffin"],
"subcategories": {
"Eggs": ["egg", "omelette", "frittata", "quiche",
"scrambled", "benedict", "shakshuka"],
"Pancakes & Waffles": ["pancake", "waffle", "crepe", "french toast"],
"Baked Goods": ["muffin", "scone", "biscuit", "quick bread",
"coffee cake", "danish"],
"Oats & Grains": ["oatmeal", "granola", "porridge", "muesli",
"overnight oats"],
},
},
"Lunch": {
"keywords": ["lunch", "sandwich", "wrap", "salad", "soup", "light meal"],
"subcategories": {
"Sandwiches": ["sandwich", "sub", "hoagie", "panini", "club",
"grilled cheese", "blt"],
"Salads": ["salad", "grain bowl", "chopped", "caesar",
"niçoise", "cobb"],
"Soups": ["soup", "bisque", "chowder", "gazpacho",
"minestrone", "lentil soup"],
"Wraps": ["wrap", "burrito bowl", "pita", "lettuce wrap",
"quesadilla"],
},
},
"Dinner": {
"keywords": ["dinner", "main dish", "entree", "main course", "supper"],
"subcategories": {
"Casseroles": ["casserole", "bake", "gratin", "lasagna",
"sheperd's pie", "pot pie"],
"Stews": ["stew", "braise", "slow cooker", "pot roast",
"daube", "ragù"],
"Grilled": ["grilled", "grill", "barbecue", "charred",
"kebab", "skewer"],
"Stir-Fries": ["stir fry", "stir-fry", "wok", "sauté",
"sauteed"],
"Roasts": ["roast", "roasted", "oven", "baked chicken",
"pot roast"],
},
},
"Snack": {
"keywords": ["snack", "appetizer", "finger food", "dip", "bite",
"starter"],
"subcategories": {
"Dips & Spreads": ["dip", "spread", "hummus", "guacamole",
"salsa", "pate"],
"Finger Foods": ["finger food", "bite", "skewer", "slider",
"wing", "nugget"],
"Chips & Crackers": ["chip", "cracker", "crisp", "popcorn",
"pretzel"],
},
},
"Dessert": {
"keywords": ["dessert", "cake", "cookie", "pie", "sweet", "pudding",
"ice cream", "brownie"],
"subcategories": {
"Cakes": ["cake", "cupcake", "layer cake", "bundt",
"cheesecake", "torte"],
"Cookies & Bars": ["cookie", "brownie", "blondie", "bar",
"biscotti", "shortbread"],
"Pies & Tarts": ["pie", "tart", "galette", "cobbler", "crisp",
"crumble"],
"Frozen": ["ice cream", "gelato", "sorbet", "frozen dessert",
"popsicle", "granita"],
"Puddings": ["pudding", "custard", "mousse", "panna cotta",
"flan", "creme brulee"],
"Candy": ["candy", "fudge", "truffle", "brittle",
"caramel", "toffee"],
},
},
"Beverage": ["drink", "smoothie", "cocktail", "beverage", "juice", "shake"],
"Side Dish": ["side dish", "side", "accompaniment", "garnish"],
"Breakfast": ["breakfast", "brunch", "eggs", "pancakes", "waffles", "oatmeal", "muffin"],
"Lunch": ["lunch", "sandwich", "wrap", "salad", "soup", "light meal"],
"Dinner": ["dinner", "main dish", "entree", "main course", "supper"],
"Snack": ["snack", "appetizer", "finger food", "dip", "bite", "starter"],
"Dessert": ["dessert", "cake", "cookie", "pie", "sweet", "pudding", "ice cream", "brownie"],
"Beverage": ["drink", "smoothie", "cocktail", "beverage", "juice", "shake"],
"Side Dish": ["side dish", "side", "accompaniment", "garnish"],
},
},
"dietary": {
@ -515,128 +56,31 @@ DOMAINS: dict[str, dict] = {
"main_ingredient": {
"label": "Main Ingredient",
"categories": {
# keywords use exact inferred_tag strings (main:X) — indexed into recipe_browser_fts.
"Chicken": {
"keywords": ["main:Chicken"],
"subcategories": {
"Baked": ["baked chicken", "roast chicken", "chicken casserole",
"chicken bake"],
"Grilled": ["grilled chicken", "chicken kebab", "bbq chicken",
"chicken skewer"],
"Fried": ["fried chicken", "chicken cutlet", "chicken schnitzel",
"crispy chicken"],
"Stewed": ["chicken stew", "chicken soup", "coq au vin",
"chicken curry", "chicken braise"],
},
},
"Beef": {
"keywords": ["main:Beef"],
"subcategories": {
"Ground Beef": ["ground beef", "hamburger", "meatball", "meatloaf",
"bolognese", "burger"],
"Steak": ["steak", "sirloin", "ribeye", "flank steak",
"filet mignon", "t-bone"],
"Roasts": ["beef roast", "pot roast", "brisket", "prime rib",
"chuck roast"],
"Stews": ["beef stew", "beef braise", "beef bourguignon",
"short ribs"],
},
},
"Pork": {
"keywords": ["main:Pork"],
"subcategories": {
"Chops": ["pork chop", "pork loin", "pork cutlet"],
"Pulled/Slow": ["pulled pork", "pork shoulder", "pork butt",
"carnitas", "slow cooker pork"],
"Sausage": ["sausage", "bratwurst", "chorizo", "andouille",
"Italian sausage"],
"Ribs": ["pork ribs", "baby back ribs", "spare ribs",
"pork belly"],
},
},
"Fish": {
"keywords": ["main:Fish"],
"subcategories": {
"Salmon": ["salmon", "smoked salmon", "gravlax"],
"Tuna": ["tuna", "albacore", "ahi"],
"White Fish": ["cod", "tilapia", "halibut", "sole", "snapper",
"flounder", "bass"],
"Shellfish": ["shrimp", "prawn", "crab", "lobster", "scallop",
"mussel", "clam", "oyster"],
},
},
"Pasta": ["main:Pasta"],
"Vegetables": {
"keywords": ["main:Vegetables"],
"subcategories": {
"Root Veg": ["potato", "sweet potato", "carrot", "beet",
"parsnip", "turnip"],
"Leafy": ["spinach", "kale", "chard", "arugula",
"collard greens", "lettuce"],
"Brassicas": ["broccoli", "cauliflower", "brussels sprouts",
"cabbage", "bok choy"],
"Nightshades": ["tomato", "eggplant", "bell pepper", "zucchini",
"squash"],
"Mushrooms": ["mushroom", "portobello", "shiitake", "oyster mushroom",
"chanterelle"],
},
},
"Eggs": ["main:Eggs"],
"Legumes": ["main:Legumes"],
"Grains": ["main:Grains"],
"Cheese": ["main:Cheese"],
"Chicken": ["chicken", "poultry", "turkey"],
"Beef": ["beef", "ground beef", "steak", "brisket", "pot roast"],
"Pork": ["pork", "bacon", "ham", "sausage", "prosciutto"],
"Fish": ["fish", "salmon", "tuna", "tilapia", "cod", "halibut", "shrimp", "seafood"],
"Pasta": ["pasta", "noodle", "spaghetti", "penne", "fettuccine", "linguine"],
"Vegetables": ["vegetable", "veggie", "cauliflower", "broccoli", "zucchini", "eggplant"],
"Eggs": ["egg", "frittata", "omelette", "omelet", "quiche"],
"Legumes": ["bean", "lentil", "chickpea", "tofu", "tempeh", "edamame"],
"Grains": ["rice", "quinoa", "barley", "farro", "oat", "grain"],
"Cheese": ["cheese", "ricotta", "mozzarella", "parmesan", "cheddar"],
},
},
}
def _get_category_def(domain: str, category: str) -> list[str] | dict | None:
"""Return the raw category definition, or None if not found."""
return DOMAINS.get(domain, {}).get("categories", {}).get(category)
def get_domain_labels() -> list[dict]:
"""Return [{id, label}] for all available domains."""
return [{"id": k, "label": v["label"]} for k, v in DOMAINS.items()]
def get_keywords_for_category(domain: str, category: str) -> list[str]:
"""Return the keyword list for the category (top-level, covers all subcategories).
For flat categories returns the list directly.
For nested categories returns the 'keywords' key.
Returns [] if category or domain not found.
"""
cat_def = _get_category_def(domain, category)
if cat_def is None:
return []
if isinstance(cat_def, list):
return cat_def
return cat_def.get("keywords", [])
def category_has_subcategories(domain: str, category: str) -> bool:
"""Return True when a category has a subcategory level."""
cat_def = _get_category_def(domain, category)
if not isinstance(cat_def, dict):
return False
return bool(cat_def.get("subcategories"))
def get_subcategory_names(domain: str, category: str) -> list[str]:
"""Return subcategory names for a category, or [] if none exist."""
cat_def = _get_category_def(domain, category)
if not isinstance(cat_def, dict):
return []
return list(cat_def.get("subcategories", {}).keys())
def get_keywords_for_subcategory(domain: str, category: str, subcategory: str) -> list[str]:
"""Return keyword list for a specific subcategory, or [] if not found."""
cat_def = _get_category_def(domain, category)
if not isinstance(cat_def, dict):
return []
return cat_def.get("subcategories", {}).get(subcategory, [])
"""Return the keyword list for a domain/category pair, or [] if not found."""
domain_data = DOMAINS.get(domain, {})
categories = domain_data.get("categories", {})
return categories.get(category, [])
def get_category_names(domain: str) -> list[str]:

View file

@ -84,9 +84,8 @@ class ElementClassifier:
name = ingredient_name.lower().strip()
if not name:
return IngredientProfile(name="", elements=[], source="heuristic")
c = self._store._cp
row = self._store._fetch_one(
f"SELECT * FROM {c}ingredient_profiles WHERE name = ?", (name,)
"SELECT * FROM ingredient_profiles WHERE name = ?", (name,)
)
if row:
return self._row_to_profile(row)

View file

@ -13,7 +13,6 @@ Walmart is kept inline until cf-core adds Impact network support:
Links are always generated (plain URLs are useful even without affiliate IDs).
Walmart links only appear when WALMART_AFFILIATE_ID is set.
Instacart and Walmart are US/CA-only; other locales get Amazon only.
"""
from __future__ import annotations
@ -24,27 +23,19 @@ from urllib.parse import quote_plus
from circuitforge_core.affiliates import wrap_url
from app.models.schemas.recipe import GroceryLink
from app.services.recipe.locale_config import get_locale
logger = logging.getLogger(__name__)
def _amazon_link(ingredient: str, locale: str) -> GroceryLink:
cfg = get_locale(locale)
def _amazon_fresh_link(ingredient: str) -> GroceryLink:
q = quote_plus(ingredient)
domain = cfg["amazon_domain"]
dept = cfg["amazon_grocery_dept"]
base = f"https://www.{domain}/s?k={q}&{dept}"
retailer = "Amazon" if locale != "us" else "Amazon Fresh"
return GroceryLink(ingredient=ingredient, retailer=retailer, url=wrap_url(base, "amazon"))
base = f"https://www.amazon.com/s?k={q}&i=amazonfresh"
return GroceryLink(ingredient=ingredient, retailer="Amazon Fresh", url=wrap_url(base, "amazon"))
def _instacart_link(ingredient: str, locale: str) -> GroceryLink:
def _instacart_link(ingredient: str) -> GroceryLink:
q = quote_plus(ingredient)
if locale == "ca":
base = f"https://www.instacart.ca/store/s?k={q}"
else:
base = f"https://www.instacart.com/store/s?k={q}"
base = f"https://www.instacart.com/store/s?k={q}"
return GroceryLink(ingredient=ingredient, retailer="Instacart", url=wrap_url(base, "instacart"))
@ -59,28 +50,26 @@ def _walmart_link(ingredient: str, affiliate_id: str) -> GroceryLink:
class GroceryLinkBuilder:
def __init__(self, tier: str = "free", has_byok: bool = False, locale: str = "us") -> None:
def __init__(self, tier: str = "free", has_byok: bool = False) -> None:
self._tier = tier
self._locale = locale
self._locale_cfg = get_locale(locale)
self._walmart_id = os.environ.get("WALMART_AFFILIATE_ID", "").strip()
def build_links(self, ingredient: str) -> list[GroceryLink]:
"""Build grocery deeplinks for a single ingredient.
Amazon link is always included, routed to the user's locale domain.
Instacart and Walmart are only shown where they operate (US/CA).
wrap_url handles affiliate ID injection for supported programs.
Amazon Fresh and Instacart links are always included; wrap_url handles
affiliate ID injection (or returns a plain URL if none is configured).
Walmart requires WALMART_AFFILIATE_ID to be set (Impact network uses a
path-based redirect that doesn't degrade cleanly to a plain URL).
"""
if not ingredient.strip():
return []
links: list[GroceryLink] = [_amazon_link(ingredient, self._locale)]
if self._locale_cfg["instacart"]:
links.append(_instacart_link(ingredient, self._locale))
if self._locale_cfg["walmart"] and self._walmart_id:
links: list[GroceryLink] = [
_amazon_fresh_link(ingredient),
_instacart_link(ingredient),
]
if self._walmart_id:
links.append(_walmart_link(ingredient, self._walmart_id))
return links

View file

@ -68,9 +68,6 @@ class LLMRecipeGenerator:
if allergy_list:
lines.append(f"IMPORTANT — must NOT contain: {', '.join(allergy_list)}")
if req.exclude_ingredients:
lines.append(f"IMPORTANT — user does not want these today: {', '.join(req.exclude_ingredients)}. Do not include them.")
lines.append("")
lines.append(f"Covered culinary elements: {', '.join(covered_elements) or 'none'}")
@ -87,13 +84,7 @@ class LLMRecipeGenerator:
if template.aromatics:
lines.append(f"Preferred aromatics: {', '.join(template.aromatics[:4])}")
unit_line = (
"Use metric units (grams, ml, Celsius) for all quantities and temperatures."
if req.unit_system == "metric"
else "Use imperial units (oz, cups, Fahrenheit) for all quantities and temperatures."
)
lines += [
unit_line,
"",
"Reply using EXACTLY this plain-text format — no markdown, no bold, no extra commentary:",
"Title: <name of the dish>",
@ -127,17 +118,8 @@ class LLMRecipeGenerator:
if allergy_list:
lines.append(f"Must NOT contain: {', '.join(allergy_list)}")
if req.exclude_ingredients:
lines.append(f"Do not use today: {', '.join(req.exclude_ingredients)}")
unit_line = (
"Use metric units (grams, ml, Celsius) for all quantities and temperatures."
if req.unit_system == "metric"
else "Use imperial units (oz, cups, Fahrenheit) for all quantities and temperatures."
)
lines += [
"Treat any mystery ingredient as a wildcard — use your imagination.",
unit_line,
"Reply using EXACTLY this plain-text format — no markdown, no bold:",
"Title: <name of the dish>",
"Ingredients: <comma-separated list>",
@ -149,15 +131,12 @@ class LLMRecipeGenerator:
return "\n".join(lines)
_SERVICE_TYPE = "vllm"
_MODEL_CANDIDATES = ["Qwen2.5-3B-Instruct", "Phi-4-mini-instruct"]
_TTL_S = 300.0
_CALLER = "kiwi-recipe"
_MODEL_CANDIDATES: list[str] = ["Ouro-2.6B-Thinking", "Ouro-1.4B"]
def _get_llm_context(self):
"""Return a sync context manager that yields an Allocation or None.
When CF_ORCH_URL is set, uses CFOrchClient to acquire a cf-text allocation
When CF_ORCH_URL is set, uses CFOrchClient to acquire a vLLM allocation
(which handles service lifecycle and VRAM). Falls back to nullcontext(None)
when the env var is absent or CFOrchClient raises on construction.
"""
@ -167,11 +146,10 @@ class LLMRecipeGenerator:
from circuitforge_orch.client import CFOrchClient
client = CFOrchClient(cf_orch_url)
return client.allocate(
service=self._SERVICE_TYPE,
service="vllm",
model_candidates=self._MODEL_CANDIDATES,
ttl_s=self._TTL_S,
caller=self._CALLER,
pipeline=os.environ.get("CF_APP_NAME") or None,
ttl_s=300.0,
caller="kiwi-recipe",
)
except Exception as exc:
logger.debug("CFOrchClient init failed, falling back to direct URL: %s", exc)
@ -190,19 +168,6 @@ class LLMRecipeGenerator:
try:
alloc = ctx.__enter__()
except Exception as exc:
msg = str(exc)
# 429 = coordinator at capacity (all nodes at max_concurrent limit).
# Don't fall back to LLMRouter — it's also overloaded and the slow
# fallback causes nginx 504s. Return "" fast so the caller degrades
# gracefully (empty recipe result) rather than timing out.
if "429" in msg or "max_concurrent" in msg.lower():
logger.info("cf-orch at capacity — returning empty result (graceful degradation)")
if ctx is not None:
try:
ctx.__exit__(None, None, None)
except Exception:
pass
return ""
logger.debug("cf-orch allocation failed, falling back to LLMRouter: %s", exc)
ctx = None # __enter__ raised — do not call __exit__

View file

@ -1,160 +0,0 @@
"""
Shopping locale configuration.
Maps a locale key to Amazon domain, currency metadata, and retailer availability.
Instacart and Walmart are US/CA-only; all other locales get Amazon only.
Amazon Fresh (&i=amazonfresh) is US-only international domains use the general
grocery department (&rh=n:16310101) where available, plain search elsewhere.
"""
from __future__ import annotations
from typing import TypedDict
class LocaleConfig(TypedDict):
amazon_domain: str
amazon_grocery_dept: str # URL fragment for grocery department on this locale's site
currency_code: str
currency_symbol: str
instacart: bool
walmart: bool
LOCALES: dict[str, LocaleConfig] = {
"us": {
"amazon_domain": "amazon.com",
"amazon_grocery_dept": "i=amazonfresh",
"currency_code": "USD",
"currency_symbol": "$",
"instacart": True,
"walmart": True,
},
"ca": {
"amazon_domain": "amazon.ca",
"amazon_grocery_dept": "rh=n:6967215011", # Grocery dept on .ca # gitleaks:allow
"currency_code": "CAD",
"currency_symbol": "CA$",
"instacart": True,
"walmart": False,
},
"gb": {
"amazon_domain": "amazon.co.uk",
"amazon_grocery_dept": "rh=n:340831031", # Grocery dept on .co.uk
"currency_code": "GBP",
"currency_symbol": "£",
"instacart": False,
"walmart": False,
},
"au": {
"amazon_domain": "amazon.com.au",
"amazon_grocery_dept": "rh=n:5765081051", # Pantry/grocery on .com.au # gitleaks:allow
"currency_code": "AUD",
"currency_symbol": "A$",
"instacart": False,
"walmart": False,
},
"nz": {
# NZ has no Amazon storefront — route to .com.au as nearest option
"amazon_domain": "amazon.com.au",
"amazon_grocery_dept": "rh=n:5765081051", # gitleaks:allow
"currency_code": "NZD",
"currency_symbol": "NZ$",
"instacart": False,
"walmart": False,
},
"de": {
"amazon_domain": "amazon.de",
"amazon_grocery_dept": "rh=n:340843031", # Lebensmittel & Getränke
"currency_code": "EUR",
"currency_symbol": "",
"instacart": False,
"walmart": False,
},
"fr": {
"amazon_domain": "amazon.fr",
"amazon_grocery_dept": "rh=n:197858031",
"currency_code": "EUR",
"currency_symbol": "",
"instacart": False,
"walmart": False,
},
"it": {
"amazon_domain": "amazon.it",
"amazon_grocery_dept": "rh=n:525616031",
"currency_code": "EUR",
"currency_symbol": "",
"instacart": False,
"walmart": False,
},
"es": {
"amazon_domain": "amazon.es",
"amazon_grocery_dept": "rh=n:599364031",
"currency_code": "EUR",
"currency_symbol": "",
"instacart": False,
"walmart": False,
},
"nl": {
"amazon_domain": "amazon.nl",
"amazon_grocery_dept": "rh=n:16584827031",
"currency_code": "EUR",
"currency_symbol": "",
"instacart": False,
"walmart": False,
},
"se": {
"amazon_domain": "amazon.se",
"amazon_grocery_dept": "rh=n:20741393031",
"currency_code": "SEK",
"currency_symbol": "kr",
"instacart": False,
"walmart": False,
},
"jp": {
"amazon_domain": "amazon.co.jp",
"amazon_grocery_dept": "rh=n:2246283051", # gitleaks:allow
"currency_code": "JPY",
"currency_symbol": "¥",
"instacart": False,
"walmart": False,
},
"in": {
"amazon_domain": "amazon.in",
"amazon_grocery_dept": "rh=n:2454178031", # gitleaks:allow
"currency_code": "INR",
"currency_symbol": "",
"instacart": False,
"walmart": False,
},
"mx": {
"amazon_domain": "amazon.com.mx",
"amazon_grocery_dept": "rh=n:10737659011",
"currency_code": "MXN",
"currency_symbol": "MX$",
"instacart": False,
"walmart": False,
},
"br": {
"amazon_domain": "amazon.com.br",
"amazon_grocery_dept": "rh=n:17878420011",
"currency_code": "BRL",
"currency_symbol": "R$",
"instacart": False,
"walmart": False,
},
"sg": {
"amazon_domain": "amazon.sg",
"amazon_grocery_dept": "rh=n:6981647051", # gitleaks:allow
"currency_code": "SGD",
"currency_symbol": "S$",
"instacart": False,
"walmart": False,
},
}
DEFAULT_LOCALE = "us"
def get_locale(key: str) -> LocaleConfig:
"""Return locale config for *key*, falling back to US if unknown."""
return LOCALES.get(key, LOCALES[DEFAULT_LOCALE])

View file

@ -21,12 +21,10 @@ if TYPE_CHECKING:
from app.db.store import Store
from app.models.schemas.recipe import GroceryLink, NutritionPanel, RecipeRequest, RecipeResult, RecipeSuggestion, SwapCandidate
from app.services.recipe.assembly_recipes import match_assembly_templates
from app.services.recipe.element_classifier import ElementClassifier
from app.services.recipe.grocery_links import GroceryLinkBuilder
from app.services.recipe.substitution_engine import SubstitutionEngine
from app.services.recipe.sensory import SensoryExclude, build_sensory_exclude, passes_sensory_filter
from app.services.recipe.time_effort import parse_time_effort
from app.services.recipe.reranker import rerank_suggestions
_LEFTOVER_DAILY_MAX_FREE = 5
@ -158,56 +156,6 @@ _PANTRY_LABEL_SYNONYMS: dict[str, str] = {
}
# When a pantry item is in a secondary state (e.g. bread → "stale"), expand
# the pantry set with terms that recipe ingredients commonly use to describe
# that state. This lets "stale bread" in a recipe ingredient match a pantry
# entry that is simply called "Bread" but is past its nominal use-by date.
# Each key is (category_in_SECONDARY_WINDOW, label_returned_by_secondary_state).
# Values are additional strings added to the pantry set for FTS coverage.
_SECONDARY_STATE_SYNONYMS: dict[tuple[str, str], list[str]] = {
# ── Existing entries (corrected) ─────────────────────────────────────────
("bread", "stale"): ["stale bread", "day-old bread", "old bread", "dried bread"],
("bakery", "day-old"): ["day-old bread", "stale bread", "stale pastry",
"day-old croissant", "stale croissant", "day-old muffin",
"stale cake", "old pastry", "day-old baguette"],
("bananas", "overripe"): ["overripe bananas", "very ripe bananas", "spotty bananas",
"brown bananas", "black bananas", "mushy bananas",
"mashed banana", "ripe bananas"],
("milk", "sour"): ["sour milk", "slightly sour milk", "buttermilk",
"soured milk", "off milk", "milk gone sour"],
("dairy", "sour"): ["sour milk", "slightly sour milk", "soured milk"],
("cheese", "rind-ready"): ["parmesan rind", "cheese rind", "aged cheese",
"hard cheese rind", "parmigiano rind", "grana padano rind",
"pecorino rind", "dry cheese"],
("rice", "day-old"): ["day-old rice", "leftover rice", "cold rice", "cooked rice",
"old rice"],
("tortillas", "stale"): ["stale tortillas", "dried tortillas", "day-old tortillas"],
# ── New entries ──────────────────────────────────────────────────────────
("apples", "soft"): ["soft apples", "mealy apples", "overripe apples",
"bruised apples", "mushy apple"],
("leafy_greens", "wilting"):["wilted spinach", "wilted greens", "limp lettuce",
"wilted kale", "tired greens"],
("tomatoes", "soft"): ["overripe tomatoes", "very ripe tomatoes", "ripe tomatoes",
"soft tomatoes", "bruised tomatoes"],
("cooked_pasta", "day-old"):["leftover pasta", "cooked pasta", "day-old pasta",
"cold pasta", "pre-cooked pasta"],
("cooked_potatoes", "day-old"): ["leftover potatoes", "cooked potatoes", "day-old potatoes",
"mashed potatoes", "baked potatoes"],
("yogurt", "tangy"): ["sour yogurt", "tangy yogurt", "past-date yogurt",
"older yogurt", "well-cultured yogurt"],
("cream", "sour"): ["slightly soured cream", "cultured cream",
"heavy cream gone sour", "soured cream"],
("wine", "open"): ["open wine", "leftover wine", "day-old wine",
"cooking wine", "red wine", "white wine"],
("cooked_beans", "day-old"):["leftover beans", "cooked beans", "day-old beans",
"cold beans", "pre-cooked beans",
"cooked chickpeas", "cooked lentils"],
("cooked_meat", "leftover"):["leftover chicken", "shredded chicken", "leftover beef",
"cooked chicken", "pulled chicken", "leftover pork",
"cooked meat", "rotisserie chicken"],
}
# Matches leading quantity/unit prefixes in recipe ingredient strings,
# e.g. "2 cups flour" → "flour", "1/2 c. ketchup" → "ketchup",
# "3 oz. butter" → "butter"
@ -337,24 +285,14 @@ def _prep_note_for(ingredient: str) -> str | None:
return template.format(ingredient=ingredient_name)
def _expand_pantry_set(
pantry_items: list[str],
secondary_pantry_items: dict[str, str] | None = None,
) -> set[str]:
def _expand_pantry_set(pantry_items: list[str]) -> set[str]:
"""Return pantry_set expanded with canonical recipe-corpus synonyms.
For each pantry item, checks _PANTRY_LABEL_SYNONYMS for substring matches
and adds the canonical form. This lets single-word recipe ingredients
("hamburger", "chicken") match product-label pantry entries
("burger patties", "rotisserie chicken").
If secondary_pantry_items is provided (product_name state label), items
in a secondary state also receive state-specific synonym expansion so that
recipe ingredients like "stale bread" or "day-old rice" are matched.
"""
from app.services.expiration_predictor import ExpirationPredictor
_predictor = ExpirationPredictor()
expanded: set[str] = set()
for item in pantry_items:
lower = item.lower().strip()
@ -362,15 +300,6 @@ def _expand_pantry_set(
for pattern, canonical in _PANTRY_LABEL_SYNONYMS.items():
if pattern in lower:
expanded.add(canonical)
# Secondary state expansion — adds terms like "stale bread", "day-old rice"
if secondary_pantry_items and item in secondary_pantry_items:
state_label = secondary_pantry_items[item]
category = _predictor.get_category_from_product(item)
if category:
synonyms = _SECONDARY_STATE_SYNONYMS.get((category, state_label), [])
expanded.update(synonyms)
return expanded
@ -588,6 +517,13 @@ def _build_source_url(row: dict) -> str | None:
return None
_ASSEMBLY_TIER_LIMITS: dict[str, int] = {
"free": 2,
"paid": 4,
"premium": 6,
}
# Method complexity classification patterns
_EASY_METHODS = re.compile(
r"\b(microwave|mix|stir|blend|toast|assemble|heat)\b", re.IGNORECASE
@ -634,34 +570,6 @@ def _hard_day_sort_tier(
return 2
def _estimate_time_min(directions: list[str], complexity: str) -> int:
"""Rough cooking time estimate from step count and method complexity.
Not precise intended for filtering and display hints only.
"""
steps = len(directions)
if complexity == "easy":
return max(5, 10 + steps * 3)
if complexity == "involved":
return max(20, 30 + steps * 6)
return max(10, 20 + steps * 4) # moderate
def _within_time(directions: list[str], max_total_min: int) -> bool:
"""Return True if parsed total time (active + passive) is within max_total_min.
Graceful degradation:
- Empty directions -> True (no data, don't hide)
- total_min == 0 (no time signals found) -> True (unparseable, don't hide)
"""
if not directions:
return True
profile = parse_time_effort(directions)
if profile.total_min == 0:
return True
return profile.total_min <= max_total_min
def _classify_method_complexity(
directions: list[str],
available_equipment: list[str] | None = None,
@ -721,8 +629,7 @@ class RecipeEngine:
profiles = self._classifier.classify_batch(req.pantry_items)
gaps = self._classifier.identify_gaps(profiles)
pantry_set = _expand_pantry_set(req.pantry_items, req.secondary_pantry_items or None)
exclude_set = _expand_pantry_set(req.exclude_ingredients) if req.exclude_ingredients else set()
pantry_set = _expand_pantry_set(req.pantry_items)
if req.level >= 3:
from app.services.recipe.llm_recipe import LLMRecipeGenerator
@ -730,11 +637,6 @@ class RecipeEngine:
return gen.generate(req, profiles, gaps)
# Level 1 & 2: deterministic path
# L1 ("Use What I Have") applies strict quality gates:
# - exclude_generic: filter catch-all recipes at the DB level
# - effective_max_missing: default to 2 when user hasn't set a cap
# - match ratio: require ≥60% ingredient coverage to avoid low-signal results
_l1 = req.level == 1 and not req.shopping_mode
nf = req.nutrition_filters
rows = self._store.search_recipes_by_ingredients(
req.pantry_items,
@ -745,22 +647,9 @@ class RecipeEngine:
max_carbs_g=nf.max_carbs_g,
max_sodium_mg=nf.max_sodium_mg,
excluded_ids=req.excluded_ids or [],
exclude_generic=_l1,
)
# L1 strict defaults: cap missing ingredients and require a minimum ratio.
_L1_MAX_MISSING_DEFAULT = 2
_L1_MIN_MATCH_RATIO = 0.6
effective_max_missing = req.max_missing
if _l1 and effective_max_missing is None:
effective_max_missing = _L1_MAX_MISSING_DEFAULT
# Load sensory preferences -- applied as silent post-score filter
_sensory_prefs_json = self._store.get_setting("sensory_preferences")
_sensory_exclude = build_sensory_exclude(_sensory_prefs_json)
suggestions = []
hard_day_tier_map: dict[int, int] = {} # recipe_id -> tier when hard_day_mode
hard_day_tier_map: dict[int, int] = {} # recipe_id → tier when hard_day_mode
for row in rows:
ingredient_names: list[str] = row.get("ingredient_names") or []
@ -770,15 +659,6 @@ class RecipeEngine:
except Exception:
ingredient_names = []
# Skip recipes that require any ingredient the user has excluded.
if exclude_set and any(_ingredient_in_pantry(n, exclude_set) for n in ingredient_names):
continue
# Sensory filter -- silent exclusion of recipes exceeding user tolerance
if not _sensory_exclude.is_empty():
if not passes_sensory_filter(row.get("sensory_tags"), _sensory_exclude):
continue
# Compute missing ingredients, detecting pantry coverage first.
# When covered, collect any prep-state annotations (e.g. "melted butter"
# → note "Melt the butter before starting.") to surface separately.
@ -810,37 +690,19 @@ class RecipeEngine:
missing.append(n)
# Filter by max_missing — skipped in shopping mode (user is willing to buy)
if not req.shopping_mode and effective_max_missing is not None and len(missing) > effective_max_missing:
if not req.shopping_mode and req.max_missing is not None and len(missing) > req.max_missing:
continue
# "Can make now" toggle: drop any recipe that still has missing ingredients
# after swaps are applied. Swapped items count as covered.
if req.pantry_match_only and missing:
continue
# L1 match ratio gate: drop results where less than 60% of the recipe's
# ingredients are in the pantry. Prevents low-signal results like a
# 10-ingredient recipe matching on only one common item.
if _l1 and ingredient_names:
match_ratio = len(matched) / len(ingredient_names)
if match_ratio < _L1_MIN_MATCH_RATIO:
continue
# Parse directions — needed for complexity, hard_day_mode, and time estimate.
directions: list[str] = row.get("directions") or []
if isinstance(directions, str):
try:
directions = json.loads(directions)
except Exception:
directions = [directions]
# Compute complexity for every suggestion (used for badge + filter).
row_complexity = _classify_method_complexity(directions, available_equipment)
row_time_min = _estimate_time_min(directions, row_complexity)
# Filter and tier-rank by hard_day_mode
if req.hard_day_mode:
if row_complexity == "involved":
directions: list[str] = row.get("directions") or []
if isinstance(directions, str):
try:
directions = json.loads(directions)
except Exception:
directions = [directions]
complexity = _classify_method_complexity(directions, available_equipment)
if complexity == "involved":
continue
hard_day_tier_map[row["id"]] = _hard_day_sort_tier(
title=row.get("title", ""),
@ -848,18 +710,6 @@ class RecipeEngine:
directions=directions,
)
# Complexity filter (#58)
if req.complexity_filter and row_complexity != req.complexity_filter:
continue
# Max time filter (#58)
if req.max_time_min is not None and row_time_min > req.max_time_min:
continue
# Total time filter (kiwi#52) — uses parsed time from directions
if req.max_total_min is not None and not _within_time(directions, req.max_total_min):
continue
# Level 2: also add dietary constraint swaps from substitution_pairs
if req.level == 2 and req.constraints:
for ing in ingredient_names:
@ -909,31 +759,41 @@ class RecipeEngine:
level=req.level,
nutrition=nutrition if has_nutrition else None,
source_url=_build_source_url(row),
complexity=row_complexity,
estimated_time_min=row_time_min,
))
# Sort corpus results.
# Paid+ tier: cross-encoder reranker orders by full pantry + dietary fit.
# Free tier (or reranker failure): overlap sort with hard_day_mode tier grouping.
reranked = rerank_suggestions(req, suggestions)
if reranked is not None:
# Reranker provided relevance order. In hard_day_mode, still respect
# tier grouping as primary sort; reranker order applies within each tier.
if req.hard_day_mode and hard_day_tier_map:
suggestions = sorted(
reranked,
key=lambda s: hard_day_tier_map.get(s.id, 1),
)
else:
suggestions = reranked
elif req.hard_day_mode and hard_day_tier_map:
# Assembly-dish templates (burrito, fried rice, pasta, etc.)
# Expiry boost: when expiry_first, the pantry_items list is already sorted
# by expiry urgency — treat the first slice as the "expiring" set so templates
# that use those items bubble up in the merged ranking.
expiring_set: set[str] = set()
if req.expiry_first:
expiring_set = _expand_pantry_set(req.pantry_items[:10])
assembly = match_assembly_templates(
pantry_items=req.pantry_items,
pantry_set=pantry_set,
excluded_ids=req.excluded_ids or [],
expiring_set=expiring_set,
)
# Cap by tier — lifted in shopping mode since missing-ingredient templates
# are desirable there (each fires an affiliate link opportunity).
if not req.shopping_mode:
assembly_limit = _ASSEMBLY_TIER_LIMITS.get(req.tier, 3)
assembly = assembly[:assembly_limit]
# Interleave: sort templates and corpus recipes together.
# Hard day mode: primary sort by tier (0=premade, 1=simple, 2=moderate),
# then by match_count within each tier. Assembly templates are inherently
# simple so they default to tier 1 when not in the tier map.
# Normal mode: sort by match_count only.
if req.hard_day_mode and hard_day_tier_map:
suggestions = sorted(
suggestions,
assembly + suggestions,
key=lambda s: (hard_day_tier_map.get(s.id, 1), -s.match_count),
)
else:
suggestions = sorted(suggestions, key=lambda s: -s.match_count)
suggestions = sorted(assembly + suggestions, key=lambda s: s.match_count, reverse=True)
# Build grocery list — deduplicated union of all missing ingredients
seen: set[str] = set()

View file

@ -1,175 +0,0 @@
"""
Reranker integration for recipe suggestions.
Wraps circuitforge_core.reranker to score recipe candidates against a
natural-language query built from the user's pantry, constraints, and
preferences. Paid+ tier only; free tier returns None (caller keeps
existing sort). All exceptions are caught and logged the reranker
must never break recipe suggestions.
Environment:
CF_RERANKER_MOCK=1 force mock backend (tests, no model required)
"""
from __future__ import annotations
import logging
from dataclasses import dataclass, field
from app.models.schemas.recipe import RecipeRequest, RecipeSuggestion
log = logging.getLogger(__name__)
# Tiers that get reranker access.
_RERANKER_TIERS: frozenset[str] = frozenset({"paid", "premium", "local"})
# Minimum candidates worth reranking — below this the cross-encoder
# overhead is not justified and the overlap sort is fine.
_MIN_CANDIDATES: int = 3
@dataclass(frozen=True)
class RerankerInput:
"""Intermediate representation passed to the reranker."""
query: str
candidates: list[str]
suggestion_ids: list[int] # parallel to candidates, for re-mapping
# ── Query builder ─────────────────────────────────────────────────────────────
def build_query(req: RecipeRequest) -> str:
"""Build a natural-language query string from the recipe request.
Encodes the user's full context so the cross-encoder can score
relevance, dietary fit, and expiry urgency in a single pass.
Only non-empty segments are included.
"""
parts: list[str] = []
if req.pantry_items:
parts.append(f"Recipe using: {', '.join(req.pantry_items)}")
if req.exclude_ingredients:
parts.append(f"Avoid: {', '.join(req.exclude_ingredients)}")
if req.allergies:
parts.append(f"Allergies: {', '.join(req.allergies)}")
if req.constraints:
parts.append(f"Dietary: {', '.join(req.constraints)}")
if req.category:
parts.append(f"Category: {req.category}")
if req.style_id:
parts.append(f"Style: {req.style_id}")
if req.complexity_filter:
parts.append(f"Prefer: {req.complexity_filter}")
if req.hard_day_mode:
parts.append("Prefer: easy, minimal effort")
# Secondary pantry items carry a state label (e.g. "stale", "overripe")
# that helps the reranker favour recipes suited to those specific states.
if req.secondary_pantry_items:
expiry_parts = [f"{name} ({state})" for name, state in req.secondary_pantry_items.items()]
parts.append(f"Use soon: {', '.join(expiry_parts)}")
elif req.expiry_first:
parts.append("Prefer: recipes that use expiring items first")
return ". ".join(parts) + "." if parts else "Recipe."
# ── Candidate builder ─────────────────────────────────────────────────────────
def build_candidate_string(suggestion: RecipeSuggestion) -> str:
"""Build a candidate string for a single recipe suggestion.
Format: "{title}. Ingredients: {comma-joined ingredients}"
Matched ingredients appear before missing ones.
Directions excluded to stay within BGE's 512-token window.
"""
ingredients = suggestion.matched_ingredients + suggestion.missing_ingredients
if not ingredients:
return suggestion.title
return f"{suggestion.title}. Ingredients: {', '.join(ingredients)}"
# ── Input assembler ───────────────────────────────────────────────────────────
def build_reranker_input(
req: RecipeRequest,
suggestions: list[RecipeSuggestion],
) -> RerankerInput:
"""Assemble query and candidate strings for the reranker."""
query = build_query(req)
candidates: list[str] = []
ids: list[int] = []
for s in suggestions:
candidates.append(build_candidate_string(s))
ids.append(s.id)
return RerankerInput(query=query, candidates=candidates, suggestion_ids=ids)
# ── cf-core seam (isolated for monkeypatching in tests) ──────────────────────
def _do_rerank(query: str, candidates: list[str], top_n: int = 0):
"""Thin wrapper around cf-core rerank(). Extracted so tests can patch it."""
from circuitforge_core.reranker import rerank
return rerank(query, candidates, top_n=top_n)
# ── Public entry point ────────────────────────────────────────────────────────
def rerank_suggestions(
req: RecipeRequest,
suggestions: list[RecipeSuggestion],
) -> list[RecipeSuggestion] | None:
"""Rerank suggestions using the cf-core cross-encoder.
Returns a reordered list with rerank_score populated, or None when:
- Tier is not paid+ (free tier keeps overlap sort)
- Fewer than _MIN_CANDIDATES suggestions (not worth the overhead)
- Any exception is raised (graceful fallback to existing sort)
The caller should treat None as "keep existing sort order".
Original suggestions are never mutated.
"""
if req.tier not in _RERANKER_TIERS:
return None
if len(suggestions) < _MIN_CANDIDATES:
return None
try:
rinput = build_reranker_input(req, suggestions)
results = _do_rerank(rinput.query, rinput.candidates, top_n=0)
# Map reranked results back to RecipeSuggestion objects using the
# candidate string as key (build_candidate_string is deterministic).
candidate_map: dict[str, RecipeSuggestion] = {
build_candidate_string(s): s for s in suggestions
}
reranked: list[RecipeSuggestion] = []
for rr in results:
suggestion = candidate_map.get(rr.candidate)
if suggestion is not None:
reranked.append(suggestion.model_copy(
update={"rerank_score": round(float(rr.score), 4)}
))
if len(reranked) < len(suggestions):
log.warning(
"Reranker lost %d/%d suggestions during mapping, falling back",
len(suggestions) - len(reranked),
len(suggestions),
)
return None
return reranked
except Exception:
log.exception("Reranker failed, falling back to overlap sort")
return None

View file

@ -1,133 +0,0 @@
"""
Sensory filter dataclass and helpers.
SensoryExclude bridges user preferences (from user_settings) to the
store browse methods and recipe engine suggest flow.
Recipes with sensory_tags = '{}' (untagged) pass ALL filters --
graceful degradation when tag_sensory_profiles.py has not run.
"""
from __future__ import annotations
import json
from dataclasses import dataclass, field
_SMELL_LEVELS: tuple[str, ...] = ("mild", "aromatic", "pungent", "fermented")
_NOISE_LEVELS: tuple[str, ...] = ("quiet", "moderate", "loud", "very_loud")
@dataclass(frozen=True)
class SensoryExclude:
"""Derived filter criteria from user sensory preferences.
textures: texture tags to exclude (empty tuple = no texture filter)
smell_above: if set, exclude recipes whose smell level is strictly above
this level in the smell spectrum
noise_above: if set, exclude recipes whose noise level is strictly above
this level in the noise spectrum
"""
textures: tuple[str, ...] = field(default_factory=tuple)
smell_above: str | None = None
noise_above: str | None = None
@classmethod
def empty(cls) -> "SensoryExclude":
"""No filtering -- pass-through for users with no preferences set."""
return cls()
def is_empty(self) -> bool:
"""True when no filtering will be applied."""
return not self.textures and self.smell_above is None and self.noise_above is None
def build_sensory_exclude(prefs_json: str | None) -> SensoryExclude:
"""Parse user_settings value for 'sensory_preferences' into a SensoryExclude.
Expected JSON shape:
{
"avoid_textures": ["mushy", "slimy"],
"max_smell": "pungent",
"max_noise": "loud"
}
Returns SensoryExclude.empty() on missing, null, or malformed input.
"""
if not prefs_json:
return SensoryExclude.empty()
try:
prefs = json.loads(prefs_json)
except (json.JSONDecodeError, TypeError):
return SensoryExclude.empty()
if not isinstance(prefs, dict):
return SensoryExclude.empty()
avoid_textures = tuple(
t for t in (prefs.get("avoid_textures") or [])
if isinstance(t, str)
)
max_smell: str | None = prefs.get("max_smell") or None
max_noise: str | None = prefs.get("max_noise") or None
if max_smell and max_smell not in _SMELL_LEVELS:
max_smell = None
if max_noise and max_noise not in _NOISE_LEVELS:
max_noise = None
return SensoryExclude(
textures=avoid_textures,
smell_above=max_smell,
noise_above=max_noise,
)
def passes_sensory_filter(
sensory_tags_raw: str | dict | None,
exclude: SensoryExclude,
) -> bool:
"""Return True if the recipe passes the sensory exclude criteria.
sensory_tags_raw: the sensory_tags column value (JSON string or already-parsed dict).
exclude: derived filter criteria.
Untagged recipes (empty dict or '{}') always pass -- graceful degradation.
Empty SensoryExclude always passes -- no preferences set.
"""
if exclude.is_empty():
return True
if sensory_tags_raw is None:
return True
if isinstance(sensory_tags_raw, str):
try:
tags: dict = json.loads(sensory_tags_raw)
except (json.JSONDecodeError, TypeError):
return True
else:
tags = sensory_tags_raw
if not tags:
return True
if exclude.textures:
recipe_textures: list[str] = tags.get("textures") or []
for t in recipe_textures:
if t in exclude.textures:
return False
if exclude.smell_above is not None:
recipe_smell: str | None = tags.get("smell")
if recipe_smell and recipe_smell in _SMELL_LEVELS:
max_idx = _SMELL_LEVELS.index(exclude.smell_above)
recipe_idx = _SMELL_LEVELS.index(recipe_smell)
if recipe_idx > max_idx:
return False
if exclude.noise_above is not None:
recipe_noise: str | None = tags.get("noise")
if recipe_noise and recipe_noise in _NOISE_LEVELS:
max_idx = _NOISE_LEVELS.index(exclude.noise_above)
recipe_idx = _NOISE_LEVELS.index(recipe_noise)
if recipe_idx > max_idx:
return False
return True

View file

@ -55,12 +55,11 @@ class SubstitutionEngine:
ingredient_name: str,
constraint: str,
) -> list[SubstitutionSwap]:
c = self._store._cp
rows = self._store._fetch_all(f"""
rows = self._store._fetch_all("""
SELECT substitute_name, constraint_label,
fat_delta, moisture_delta, glutamate_delta, protein_delta,
occurrence_count, compensation_hints
FROM {c}substitution_pairs
FROM substitution_pairs
WHERE original_name = ? AND constraint_label = ?
ORDER BY occurrence_count DESC
""", (ingredient_name.lower(), constraint))

View file

@ -1,325 +0,0 @@
"""
Recipe tag inference engine.
Derives normalized tags from a recipe's title, ingredient names, existing corpus
tags (category + keywords), enriched ingredient profile data, and optional
nutrition data.
Tags are organized into five namespaces:
cuisine:* -- cuisine/region classification
dietary:* -- dietary restriction / nutrition profile
flavor:* -- flavor profile (spicy, smoky, sweet, etc.)
time:* -- effort / time signals
meal:* -- meal type
can_be:* -- achievable with substitutions (e.g. can_be:Gluten-Free)
Output is a flat sorted list of strings, e.g.:
["can_be:Gluten-Free", "cuisine:Italian", "dietary:Low-Carb",
"flavor:Savory", "flavor:Umami", "time:Quick"]
These populate recipes.inferred_tags and are FTS5-indexed so browse domain
queries find recipes the food.com corpus tags alone would miss.
"""
from __future__ import annotations
# ---------------------------------------------------------------------------
# Text-signal tables
# (tag, [case-insensitive substrings to search in combined title+ingredient text])
# ---------------------------------------------------------------------------
_CUISINE_SIGNALS: list[tuple[str, list[str]]] = [
("cuisine:Japanese", ["miso", "dashi", "ramen", "sushi", "teriyaki", "sake", "mirin",
"wasabi", "panko", "edamame", "tonkatsu", "yakitori", "ponzu"]),
("cuisine:Korean", ["gochujang", "kimchi", "doenjang", "gochugaru",
"bulgogi", "bibimbap", "japchae"]),
("cuisine:Thai", ["fish sauce", "lemongrass", "galangal", "pad thai", "thai basil",
"kaffir lime", "tom yum", "green curry", "red curry", "nam pla"]),
("cuisine:Chinese", ["hoisin", "oyster sauce", "five spice", "bok choy", "chow mein",
"dumpling", "wonton", "mapo", "char siu", "sichuan"]),
("cuisine:Vietnamese", ["pho", "banh mi", "nuoc cham", "rice paper", "vietnamese"]),
("cuisine:Indian", ["garam masala", "turmeric", "cardamom", "fenugreek", "paneer",
"tikka", "masala", "biryani", "dal", "naan", "tandoori",
"curry leaf", "tamarind", "chutney"]),
("cuisine:Middle Eastern", ["tahini", "harissa", "za'atar", "sumac", "baharat", "rose water",
"pomegranate molasses", "freekeh", "fattoush", "shakshuka"]),
("cuisine:Greek", ["feta", "tzatziki", "moussaka", "spanakopita", "orzo",
"kalamata", "gyro", "souvlaki", "dolma"]),
("cuisine:Mediterranean", ["hummus", "pita", "couscous", "preserved lemon"]),
("cuisine:Italian", ["pasta", "pizza", "risotto", "lasagna", "carbonara", "gnocchi",
"parmesan", "mozzarella", "ricotta", "prosciutto", "pancetta",
"arancini", "osso buco", "tiramisu", "pesto", "bolognese",
"cannoli", "polenta", "bruschetta", "focaccia"]),
("cuisine:French", ["croissant", "quiche", "crepe", "coq au vin",
"ratatouille", "bearnaise", "hollandaise", "bouillabaisse",
"herbes de provence", "dijon", "gruyere", "brie", "cassoulet"]),
("cuisine:Spanish", ["paella", "chorizo", "gazpacho", "tapas", "patatas bravas",
"sofrito", "manchego", "albondigas"]),
("cuisine:German", ["sauerkraut", "bratwurst", "schnitzel", "pretzel", "strudel",
"spaetzle", "sauerbraten"]),
("cuisine:Mexican", ["taco", "burrito", "enchilada", "salsa", "guacamole", "chipotle",
"queso", "tamale", "mole", "jalapeno", "tortilla", "carnitas",
"chile verde", "posole", "tostada", "quesadilla"]),
("cuisine:Latin American", ["plantain", "yuca", "chimichurri", "ceviche", "adobo", "empanada"]),
("cuisine:American", ["bbq sauce", "buffalo sauce", "ranch dressing", "coleslaw",
"cornbread", "mac and cheese", "brisket", "cheeseburger"]),
("cuisine:Southern", ["collard greens", "black-eyed peas", "okra", "grits", "catfish",
"hush puppies", "pecan pie"]),
("cuisine:Cajun", ["cajun", "creole", "gumbo", "jambalaya", "andouille", "etouffee"]),
("cuisine:African", ["injera", "berbere", "jollof", "suya", "egusi", "fufu", "tagine"]),
("cuisine:Caribbean", ["jerk", "scotch bonnet", "callaloo", "ackee"]),
# BBQ detection: match on title terms and key ingredients; these rarely appear
# in food.com's own keyword/category taxonomy so we derive the tag from content.
("cuisine:BBQ", ["brisket", "pulled pork", "spare ribs", "baby back ribs",
"baby back", "burnt ends", "pit smoked", "smoke ring",
"low and slow", "hickory", "mesquite", "liquid smoke",
"bbq brisket", "smoked brisket", "barbecue brisket",
"carolina bbq", "texas bbq", "kansas city bbq",
"memphis bbq", "smoked ribs", "smoked pulled pork",
"dry rub ribs", "wet rub ribs", "beer can chicken smoked"]),
]
_DIETARY_SIGNALS: list[tuple[str, list[str]]] = [
("dietary:Vegan", ["vegan", "plant-based", "plant based"]),
("dietary:Vegetarian", ["vegetarian", "meatless"]),
("dietary:Gluten-Free", ["gluten-free", "gluten free", "celiac"]),
("dietary:Dairy-Free", ["dairy-free", "dairy free", "lactose free", "non-dairy"]),
("dietary:Low-Carb", ["low-carb", "low carb", "keto", "ketogenic", "very low carbs"]),
("dietary:High-Protein", ["high protein", "high-protein"]),
("dietary:Low-Fat", ["low-fat", "low fat", "fat-free", "reduced fat"]),
("dietary:Paleo", ["paleo", "whole30"]),
("dietary:Nut-Free", ["nut-free", "nut free", "peanut free"]),
("dietary:Egg-Free", ["egg-free", "egg free"]),
("dietary:Low-Sodium", ["low sodium", "no salt"]),
("dietary:Healthy", ["healthy", "low cholesterol", "heart healthy", "wholesome"]),
]
_FLAVOR_SIGNALS: list[tuple[str, list[str]]] = [
("flavor:Spicy", ["jalapeno", "habanero", "ghost pepper", "sriracha",
"chili flake", "red pepper flake", "cayenne", "hot sauce",
"gochujang", "harissa", "scotch bonnet", "szechuan pepper", "spicy"]),
("flavor:Smoky", ["smoked", "liquid smoke", "smoked paprika",
"bbq sauce", "barbecue", "hickory", "mesquite"]),
("flavor:Sweet", ["honey", "maple syrup", "brown sugar", "caramel", "chocolate",
"vanilla", "condensed milk", "molasses", "agave"]),
("flavor:Savory", ["soy sauce", "fish sauce", "miso", "worcestershire", "anchovy",
"parmesan", "blue cheese", "bone broth"]),
("flavor:Tangy", ["lemon juice", "lime juice", "vinegar", "balsamic", "buttermilk",
"sour cream", "fermented", "pickled", "tamarind", "sumac"]),
("flavor:Herby", ["fresh basil", "fresh cilantro", "fresh dill", "fresh mint",
"fresh tarragon", "fresh thyme", "herbes de provence"]),
("flavor:Rich", ["heavy cream", "creme fraiche", "mascarpone", "double cream",
"ghee", "coconut cream", "cream cheese"]),
("flavor:Umami", ["mushroom", "nutritional yeast", "tomato paste",
"parmesan rind", "bonito", "kombu"]),
]
_TIME_SIGNALS: list[tuple[str, list[str]]] = [
("time:Quick", ["< 15 mins", "< 30 mins", "weeknight", "easy"]),
("time:Under 1 Hour", ["< 60 mins"]),
("time:Make-Ahead", ["freezer", "overnight", "refrigerator", "make-ahead", "make ahead"]),
("time:Slow Cook", ["slow cooker", "crockpot", "< 4 hours", "braise"]),
]
_MAIN_INGREDIENT_SIGNALS: list[tuple[str, list[str]]] = [
("main:Chicken", ["chicken", "poultry", "turkey"]),
("main:Beef", ["beef", "ground beef", "steak", "brisket", "pot roast"]),
("main:Pork", ["pork", "bacon", "ham", "sausage", "prosciutto"]),
("main:Fish", ["salmon", "tuna", "tilapia", "cod", "halibut", "shrimp", "seafood", "fish"]),
("main:Pasta", ["pasta", "noodle", "spaghetti", "penne", "fettuccine", "linguine"]),
("main:Vegetables", ["broccoli", "cauliflower", "zucchini", "eggplant", "carrot",
"vegetable", "veggie"]),
("main:Eggs", ["egg", "frittata", "omelette", "omelet", "quiche"]),
("main:Legumes", ["bean", "lentil", "chickpea", "tofu", "tempeh", "edamame"]),
("main:Grains", ["rice", "quinoa", "barley", "farro", "oat", "grain"]),
("main:Cheese", ["cheddar", "mozzarella", "parmesan", "ricotta", "brie",
"cheese"]),
]
# food.com corpus tag -> normalized tags
_CORPUS_TAG_MAP: dict[str, list[str]] = {
"european": ["cuisine:Italian", "cuisine:French", "cuisine:German",
"cuisine:Spanish"],
"asian": ["cuisine:Chinese", "cuisine:Japanese", "cuisine:Thai",
"cuisine:Korean", "cuisine:Vietnamese"],
"chinese": ["cuisine:Chinese"],
"japanese": ["cuisine:Japanese"],
"thai": ["cuisine:Thai"],
"vietnamese": ["cuisine:Vietnamese"],
"indian": ["cuisine:Indian"],
"greek": ["cuisine:Greek"],
"mexican": ["cuisine:Mexican"],
"african": ["cuisine:African"],
"caribbean": ["cuisine:Caribbean"],
"vegan": ["dietary:Vegan", "dietary:Vegetarian"],
"vegetarian": ["dietary:Vegetarian"],
"healthy": ["dietary:Healthy"],
"low cholesterol": ["dietary:Healthy"],
"very low carbs": ["dietary:Low-Carb"],
"high in...": ["dietary:High-Protein"],
"lactose free": ["dietary:Dairy-Free"],
"egg free": ["dietary:Egg-Free"],
"< 15 mins": ["time:Quick"],
"< 30 mins": ["time:Quick"],
"< 60 mins": ["time:Under 1 Hour"],
"< 4 hours": ["time:Slow Cook"],
"weeknight": ["time:Quick"],
"freezer": ["time:Make-Ahead"],
"dessert": ["meal:Dessert"],
"breakfast": ["meal:Breakfast"],
"lunch/snacks": ["meal:Lunch", "meal:Snack"],
"beverages": ["meal:Beverage"],
"cookie & brownie": ["meal:Dessert"],
"breads": ["meal:Bread"],
}
# ingredient_profiles.elements value -> flavor tag
_ELEMENT_TO_FLAVOR: dict[str, str] = {
"Aroma": "flavor:Herby",
"Richness": "flavor:Rich",
"Structure": "", # no flavor tag
"Binding": "",
"Crust": "flavor:Smoky",
"Lift": "",
"Emulsion": "flavor:Rich",
"Acid": "flavor:Tangy",
}
def _build_text(title: str, ingredient_names: list[str]) -> str:
parts = [title.lower()]
parts.extend(i.lower() for i in ingredient_names)
return " ".join(parts)
def _match_signals(text: str, table: list[tuple[str, list[str]]]) -> list[str]:
return [tag for tag, pats in table if any(p in text for p in pats)]
def infer_tags(
title: str,
ingredient_names: list[str],
corpus_keywords: list[str],
corpus_category: str = "",
# Enriched ingredient profile signals (from ingredient_profiles cross-ref)
element_coverage: dict[str, float] | None = None,
fermented_count: int = 0,
glutamate_total: float = 0.0,
ph_min: float | None = None,
available_sub_constraints: list[str] | None = None,
# Nutrition data for macro-based tags
calories: float | None = None,
protein_g: float | None = None,
fat_g: float | None = None,
carbs_g: float | None = None,
servings: float | None = None,
) -> list[str]:
"""
Derive normalized tags for a recipe.
Parameters
----------
title, ingredient_names, corpus_keywords, corpus_category
: Primary recipe data.
element_coverage
: Dict from recipes.element_coverage -- element name to coverage ratio
(e.g. {"Aroma": 0.6, "Richness": 0.4}). Derived from ingredient_profiles.
fermented_count
: Number of fermented ingredients (from ingredient_profiles.is_fermented).
glutamate_total
: Sum of glutamate_mg across all profiled ingredients. High values signal umami.
ph_min
: Minimum ph_estimate across profiled ingredients. Low values signal acidity.
available_sub_constraints
: Substitution constraint labels achievable for this recipe
(e.g. ["gluten_free", "low_carb"]). From substitution_pairs cross-ref.
These become can_be:* tags.
calories, protein_g, fat_g, carbs_g, servings
: Nutrition data for macro-based dietary tags.
Returns
-------
Sorted list of unique normalized tag strings.
"""
tags: set[str] = set()
# 1. Map corpus tags to normalized vocabulary
for kw in corpus_keywords:
for t in _CORPUS_TAG_MAP.get(kw.lower(), []):
tags.add(t)
if corpus_category:
for t in _CORPUS_TAG_MAP.get(corpus_category.lower(), []):
tags.add(t)
# 2. Text-signal matching
text = _build_text(title, ingredient_names)
tags.update(_match_signals(text, _CUISINE_SIGNALS))
tags.update(_match_signals(text, _DIETARY_SIGNALS))
tags.update(_match_signals(text, _FLAVOR_SIGNALS))
tags.update(_match_signals(text, _MAIN_INGREDIENT_SIGNALS))
# 3. Time signals from corpus keywords + text
corpus_text = " ".join(kw.lower() for kw in corpus_keywords)
tags.update(_match_signals(corpus_text, _TIME_SIGNALS))
tags.update(_match_signals(text, _TIME_SIGNALS))
# 4. Enriched profile signals
if element_coverage:
for element, coverage in element_coverage.items():
if coverage > 0.2: # >20% of ingredients carry this element
flavor_tag = _ELEMENT_TO_FLAVOR.get(element, "")
if flavor_tag:
tags.add(flavor_tag)
if glutamate_total > 50:
tags.add("flavor:Umami")
if fermented_count > 0:
tags.add("flavor:Tangy")
if ph_min is not None and ph_min < 4.5:
tags.add("flavor:Tangy")
# 5. Achievable-via-substitution tags
if available_sub_constraints:
label_to_tag = {
"gluten_free": "can_be:Gluten-Free",
"low_calorie": "can_be:Low-Calorie",
"low_carb": "can_be:Low-Carb",
"vegan": "can_be:Vegan",
"dairy_free": "can_be:Dairy-Free",
"low_sodium": "can_be:Low-Sodium",
}
for label in available_sub_constraints:
tag = label_to_tag.get(label)
if tag:
tags.add(tag)
# 6. Macro-based dietary tags
if servings and servings > 0 and any(
v is not None for v in (protein_g, fat_g, carbs_g, calories)
):
def _per(v: float | None) -> float | None:
return v / servings if v is not None else None
prot_s = _per(protein_g)
fat_s = _per(fat_g)
carb_s = _per(carbs_g)
cal_s = _per(calories)
if prot_s is not None and prot_s >= 20:
tags.add("dietary:High-Protein")
if fat_s is not None and fat_s <= 5:
tags.add("dietary:Low-Fat")
if carb_s is not None and carb_s <= 10:
tags.add("dietary:Low-Carb")
if cal_s is not None and cal_s <= 250:
tags.add("dietary:Light")
elif protein_g is not None and protein_g >= 20:
tags.add("dietary:High-Protein")
# 7. Vegan implies vegetarian
if "dietary:Vegan" in tags:
tags.add("dietary:Vegetarian")
return sorted(tags)

View file

@ -1,197 +0,0 @@
"""
Runtime parser for active/passive time split and equipment detection.
Operates over a list of direction strings. No I/O pure Python functions.
Sub-millisecond for up to 20 recipes (20 × ~10 steps each = 200 regex calls).
"""
from __future__ import annotations
import math
import re
from dataclasses import dataclass
from typing import Final
# ── Passive step keywords (whole-word, case-insensitive) ──────────────────
_PASSIVE_PATTERNS: Final[list[str]] = [
"simmer", "bake", "roast", "broil", "refrigerate", "marinate",
"chill", "cool", "freeze", "rest", "stand", "set", "soak",
"steep", "proof", "rise", "let", "wait", "overnight", "braise",
r"slow\s+cook", r"pressure\s+cook",
]
# Pre-compiled as a single alternation — avoids re-compiling on every call.
_PASSIVE_RE: re.Pattern[str] = re.compile(
r"\b(?:" + "|".join(_PASSIVE_PATTERNS) + r")\b",
re.IGNORECASE,
)
# ── Time extraction regex ─────────────────────────────────────────────────
# Two-branch pattern:
# Branch A (groups 1-3): range "15-20 minutes", "1520 min"
# Branch B (groups 4-5): single "10 minutes", "2 hours", "30 sec"
#
# Separator characters: plain hyphen (-), en-dash (), or literal "-to-"
_TIME_RE: re.Pattern[str] = re.compile(
r"(\d+)\s*(?:[-\u2013]|-to-)\s*(\d+)\s*(hour|hr|minute|min|second|sec)s?"
r"|"
r"(\d+)\s*(hour|hr|minute|min|second|sec)s?",
re.IGNORECASE,
)
_MAX_MINUTES_PER_STEP: Final[int] = 480 # 8 hours sanity cap
# ── Equipment detection (keyword → label, in detection priority order) ────
_EQUIPMENT_RULES: Final[list[tuple[re.Pattern[str], str]]] = [
(re.compile(r"\b(?:chop|dice|mince|slice|julienne)\b", re.IGNORECASE), "Knife"),
(re.compile(r"\b(?:skillet|sauté|saute|fry|sear|pan-fry|pan fry)\b", re.IGNORECASE), "Skillet"),
(re.compile(r"\b(?:wooden spoon|spatula|stir|fold)\b", re.IGNORECASE), "Spoon"),
(re.compile(r"\b(?:pot|boil|simmer|blanch|stock)\b", re.IGNORECASE), "Pot"),
(re.compile(r"\b(?:oven|bake|roast|preheat|broil)\b", re.IGNORECASE), "Oven"),
(re.compile(r"\b(?:blender|blend|purée|puree|food processor)\b", re.IGNORECASE), "Blender"),
(re.compile(r"\b(?:stand mixer|hand mixer|whip|beat)\b", re.IGNORECASE), "Mixer"),
(re.compile(r"\b(?:grill|barbecue|char|griddle)\b", re.IGNORECASE), "Grill"),
(re.compile(r"\b(?:slow cooker|crockpot|low and slow)\b", re.IGNORECASE), "Slow cooker"),
(re.compile(r"\b(?:pressure cooker|instant pot)\b", re.IGNORECASE), "Pressure cooker"),
(re.compile(r"\b(?:drain|strain|colander|rinse pasta)\b", re.IGNORECASE), "Colander"),
]
# ── Dataclasses ───────────────────────────────────────────────────────────
@dataclass(frozen=True)
class StepAnalysis:
"""Analysis result for a single direction step."""
is_passive: bool
detected_minutes: int | None # None when no time mention found in text
@dataclass(frozen=True)
class TimeEffortProfile:
"""Aggregated time and effort profile for a full recipe."""
active_min: int # total minutes requiring active attention
passive_min: int # total minutes the cook can step away
total_min: int # active_min + passive_min
step_analyses: list[StepAnalysis] # one entry per direction step
equipment: list[str] # ordered, deduplicated equipment labels
effort_label: str # "quick" | "moderate" | "involved"
# ── Core parsing logic ────────────────────────────────────────────────────
def _extract_minutes(text: str) -> int | None:
"""Return the number of minutes mentioned in text, or None.
Range values (e.g. "15-20 minutes") return the integer midpoint.
Hours are converted to minutes. Seconds are rounded up to 1 minute minimum.
Result is capped at _MAX_MINUTES_PER_STEP.
"""
m = _TIME_RE.search(text)
if m is None:
return None
if m.group(1) is not None:
# Branch A: range match (e.g. "15-20 minutes")
low = int(m.group(1))
high = int(m.group(2))
unit = m.group(3).lower()
raw_value: float = (low + high) / 2
else:
# Branch B: single value match (e.g. "10 minutes")
low = int(m.group(4))
unit = m.group(5).lower()
raw_value = float(low)
if unit in ("hour", "hr"):
minutes: float = raw_value * 60
elif unit in ("second", "sec"):
minutes = max(1.0, math.ceil(raw_value / 60))
else:
minutes = raw_value
return min(int(minutes), _MAX_MINUTES_PER_STEP)
def _classify_passive(text: str) -> bool:
"""Return True if the step text matches any passive keyword (whole-word)."""
return _PASSIVE_RE.search(text) is not None
def _detect_equipment(all_text: str, has_passive: bool) -> list[str]:
"""Return ordered, deduplicated list of equipment labels detected in text.
all_text should be all direction steps joined with spaces.
has_passive controls whether 'Timer' is appended at the end.
"""
seen: set[str] = set()
result: list[str] = []
for pattern, label in _EQUIPMENT_RULES:
if label not in seen and pattern.search(all_text):
seen.add(label)
result.append(label)
if has_passive and "Timer" not in seen:
result.append("Timer")
return result
def _effort_label(step_count: int) -> str:
"""Derive effort label from step count."""
if step_count <= 3:
return "quick"
if step_count <= 7:
return "moderate"
return "involved"
def parse_time_effort(directions: list[str]) -> TimeEffortProfile:
"""Parse a list of direction strings into a TimeEffortProfile.
Returns a zero-value profile with empty lists when directions is empty.
Never raises all failures silently produce sensible defaults.
"""
if not directions:
return TimeEffortProfile(
active_min=0,
passive_min=0,
total_min=0,
step_analyses=[],
equipment=[],
effort_label="quick",
)
step_analyses: list[StepAnalysis] = []
active_min = 0
passive_min = 0
has_any_passive = False
for step in directions:
is_passive = _classify_passive(step)
detected = _extract_minutes(step)
if is_passive:
has_any_passive = True
if detected is not None:
passive_min += detected
else:
if detected is not None:
active_min += detected
step_analyses.append(StepAnalysis(
is_passive=is_passive,
detected_minutes=detected,
))
combined_text = " ".join(directions)
equipment = _detect_equipment(combined_text, has_any_passive)
return TimeEffortProfile(
active_min=active_min,
passive_min=passive_min,
total_min=active_min + passive_min,
step_analyses=step_analyses,
equipment=equipment,
effort_label=_effort_label(len(directions)),
)

View file

@ -22,7 +22,7 @@ from app.services.expiration_predictor import ExpirationPredictor
log = logging.getLogger(__name__)
LLM_TASK_TYPES: frozenset[str] = frozenset({"expiry_llm_fallback", "recipe_llm"})
LLM_TASK_TYPES: frozenset[str] = frozenset({"expiry_llm_fallback"})
VRAM_BUDGETS: dict[str, float] = {
# ExpirationPredictor uses a small LLM (16 tokens out, single pass).
@ -88,8 +88,6 @@ def run_task(
try:
if task_type == "expiry_llm_fallback":
_run_expiry_llm_fallback(db_path, job_id, params)
elif task_type == "recipe_llm":
_run_recipe_llm(db_path, job_id, params)
else:
raise ValueError(f"Unknown kiwi task type: {task_type!r}")
_update_task_status(db_path, task_id, "completed")
@ -145,41 +143,3 @@ def _run_expiry_llm_fallback(
expiry,
days,
)
def _run_recipe_llm(db_path: Path, _job_id_int: int, params: str | None) -> None:
"""Run LLM recipe generation for an async recipe job.
params JSON keys:
job_id (required) recipe_jobs.job_id string (e.g. "rec_a1b2c3...")
Creates its own Store follows same pattern as _suggest_in_thread.
MUST call store.fail_recipe_job() before re-raising so recipe_jobs.status
doesn't stay 'running' while background_tasks shows 'failed'.
"""
from app.db.store import Store
from app.models.schemas.recipe import RecipeRequest
from app.services.recipe.recipe_engine import RecipeEngine
p = json.loads(params or "{}")
recipe_job_id: str = p.get("job_id", "")
if not recipe_job_id:
raise ValueError("recipe_llm: 'job_id' is required in params")
store = Store(db_path)
try:
store.update_recipe_job_running(recipe_job_id)
row = store._fetch_one(
"SELECT request FROM recipe_jobs WHERE job_id=?", (recipe_job_id,)
)
if row is None:
raise ValueError(f"recipe_llm: recipe_jobs row not found: {recipe_job_id!r}")
req = RecipeRequest.model_validate_json(row["request"])
result = RecipeEngine(store).suggest(req)
store.complete_recipe_job(recipe_job_id, result.model_dump_json())
log.info("recipe_llm: job %s completed (%d suggestion(s))", recipe_job_id, len(result.suggestions))
except Exception as exc:
store.fail_recipe_job(recipe_job_id, str(exc))
raise
finally:
store.close()

View file

@ -1,10 +1,5 @@
# app/tasks/scheduler.py
"""Kiwi LLM task scheduler — thin shim over circuitforge_core.tasks.scheduler.
Local mode (CLOUD_MODE unset): LocalScheduler simple FIFO, no coordinator.
Cloud mode (CLOUD_MODE=true): OrchestratedScheduler coordinator-aware, fans
out concurrent jobs across all registered cf-orch GPU nodes.
"""
"""Kiwi LLM task scheduler — thin shim over circuitforge_core.tasks.scheduler."""
from __future__ import annotations
from pathlib import Path
@ -12,68 +7,15 @@ from pathlib import Path
from circuitforge_core.tasks.scheduler import (
TaskScheduler,
get_scheduler as _base_get_scheduler,
reset_scheduler as _reset_local, # re-export for tests
reset_scheduler, # re-export for tests
)
from app.cloud_session import CLOUD_MODE
from app.core.config import settings
from app.tasks.runner import LLM_TASK_TYPES, VRAM_BUDGETS, run_task
def _orch_available() -> bool:
"""Return True if circuitforge_orch is installed in this environment."""
try:
import circuitforge_orch # noqa: F401
return True
except ImportError:
return False
def _use_orch() -> bool:
"""Return True if the OrchestratedScheduler should be used.
Priority order:
1. USE_ORCH_SCHEDULER env var explicit override always wins.
2. CLOUD_MODE=true use orch in managed cloud deployments.
3. circuitforge_orch installed paid+ local users who have cf-orch
set up get coordinator-aware scheduling (local GPU first) automatically.
"""
override = settings.USE_ORCH_SCHEDULER
if override is not None:
return override
return CLOUD_MODE or _orch_available()
def get_scheduler(db_path: Path) -> TaskScheduler:
"""Return the process-level TaskScheduler singleton for Kiwi.
OrchestratedScheduler: coordinator-aware, fans out concurrent jobs across
all registered cf-orch GPU nodes. Active when USE_ORCH_SCHEDULER=true,
CLOUD_MODE=true, or circuitforge_orch is installed locally (paid+ users
running their own cf-orch stack get this automatically; local GPU is
preferred by the coordinator's allocation queue).
LocalScheduler: serial FIFO, no coordinator dependency. Free-tier local
installs without circuitforge_orch installed use this automatically.
"""
if _use_orch():
try:
from circuitforge_orch.scheduler import get_orch_scheduler
except ImportError:
import logging
logging.getLogger(__name__).warning(
"circuitforge_orch not installed — falling back to LocalScheduler"
)
else:
return get_orch_scheduler(
db_path=db_path,
run_task_fn=run_task,
task_types=LLM_TASK_TYPES,
vram_budgets=VRAM_BUDGETS,
coordinator_url=settings.COORDINATOR_URL,
service_name="kiwi",
)
"""Return the process-level TaskScheduler singleton for Kiwi."""
return _base_get_scheduler(
db_path=db_path,
run_task_fn=run_task,
@ -82,15 +24,3 @@ def get_scheduler(db_path: Path) -> TaskScheduler:
coordinator_url=settings.COORDINATOR_URL,
service_name="kiwi",
)
def reset_scheduler() -> None:
"""Shut down and clear the active scheduler singleton. TEST TEARDOWN ONLY."""
if _use_orch():
try:
from circuitforge_orch.scheduler import reset_orch_scheduler
reset_orch_scheduler()
return
except ImportError:
pass
_reset_local()

View file

@ -18,19 +18,9 @@ KIWI_BYOK_UNLOCKABLE: frozenset[str] = frozenset({
"style_classifier",
"meal_plan_llm",
"meal_plan_llm_timing",
"community_fork_adapt",
"community_fork_adapt", # Fork a community plan with LLM pantry adaptation
})
# Sources subject to monthly cf-orch call caps. Subscription-based sources are uncapped.
LIFETIME_SOURCES: frozenset[str] = frozenset({"lifetime", "founders"})
# (source, tier) → monthly cf-orch call allowance
LIFETIME_ORCH_CAPS: dict[tuple[str, str], int] = {
("lifetime", "paid"): 60,
("lifetime", "premium"): 180,
("founders", "premium"): 300,
}
# Feature → minimum tier required
KIWI_FEATURES: dict[str, str] = {
# Free tier
@ -44,7 +34,6 @@ KIWI_FEATURES: dict[str, str] = {
# Paid tier
"receipt_ocr": "paid", # BYOK-unlockable
"visual_label_capture": "paid", # Camera capture for unenriched barcodes (kiwi#79)
"recipe_suggestions": "paid", # BYOK-unlockable
"expiry_llm_matching": "paid", # BYOK-unlockable
"meal_planning": "free",
@ -55,8 +44,11 @@ KIWI_FEATURES: dict[str, str] = {
"style_picker": "paid",
"recipe_collections": "paid",
"style_classifier": "paid", # LLM auto-tag for saved recipe style tags; BYOK-unlockable
# Community (free to browse, paid to publish/fork)
"community_browse": "free", # Read-only feed access
"community_publish": "paid", # Publish plans/outcomes to community feed
"community_fork_adapt": "paid", # Fork with LLM pantry adaptation (BYOK-unlockable)
"community_fork_adapt": "paid", # Fork a plan with LLM pantry adaptation; BYOK-unlockable
# Premium tier
"multi_household": "premium",

View file

@ -13,7 +13,6 @@ services:
environment:
CLOUD_MODE: "true"
CLOUD_DATA_ROOT: /devl/kiwi-cloud-data
RECIPE_DB_PATH: /devl/kiwi-corpus/recipes.db
KIWI_BASE_URL: https://menagerie.circuitforge.tech/kiwi
# DIRECTUS_JWT_SECRET, HEIMDALL_URL, HEIMDALL_ADMIN_TOKEN — set in .env
# DEV ONLY: comma-separated IPs that bypass JWT auth (LAN testing without Caddy).
@ -21,21 +20,10 @@ services:
CLOUD_AUTH_BYPASS_IPS: ${CLOUD_AUTH_BYPASS_IPS:-}
# cf-orch: route LLM calls through the coordinator for managed GPU inference
CF_ORCH_URL: http://host.docker.internal:7700
# Product identifier for coordinator analytics — per-product VRAM/request breakdown
CF_APP_NAME: kiwi
# cf-orch streaming proxy — coordinator URL + product key for /proxy/authorize
# COORDINATOR_KIWI_KEY must be set in .env (never commit the value)
COORDINATOR_URL: http://10.1.10.71:7700
COORDINATOR_KIWI_KEY: ${COORDINATOR_KIWI_KEY:-}
# Community PostgreSQL — shared across CF products; unset = community features unavailable (fail soft)
COMMUNITY_DB_URL: ${COMMUNITY_DB_URL:-}
COMMUNITY_PSEUDONYM_SALT: ${COMMUNITY_PSEUDONYM_SALT:-}
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- /devl/kiwi-cloud-data:/devl/kiwi-cloud-data
# Recipe corpus — shared read-only NFS-backed SQLite (3.1M recipes, 2.9GB)
- /Library/Assets/kiwi/kiwi.db:/devl/kiwi-corpus/recipes.db:ro
# LLM config — shared with other CF products; read-only in container
- ${HOME}/.config/circuitforge:/root/.config/circuitforge:ro
networks:

View file

@ -8,6 +8,23 @@ services:
# Docker can follow the symlink inside the container.
- /Library/Assets/kiwi:/Library/Assets/kiwi:rw
# cf-orch agent sidecar removed 2026-04-24: Sif is now a dedicated compute node
# with its own systemd cf-orch-agent service (port 7703, advertise-host 10.1.10.158).
# This sidecar was only valid when Kiwi ran on Sif directly.
# cf-orch agent sidecar: registers kiwi as a GPU node with the coordinator.
# The API scheduler uses COORDINATOR_URL to lease VRAM cooperatively; this
# agent makes kiwi's VRAM usage visible on the orchestrator dashboard.
cf-orch-agent:
image: kiwi-api # reuse local api image — cf-core already installed there
network_mode: host
env_file: .env
environment:
# Override coordinator URL here or via .env
COORDINATOR_URL: ${COORDINATOR_URL:-http://10.1.10.71:7700}
command: >
conda run -n kiwi cf-orch agent
--coordinator ${COORDINATOR_URL:-http://10.1.10.71:7700}
--node-id kiwi
--host 0.0.0.0
--port 7702
--advertise-host ${CF_ORCH_ADVERTISE_HOST:-10.1.10.71}
restart: unless-stopped
depends_on:
- api

View file

@ -1,74 +0,0 @@
# Kiwi — LLM backend configuration
#
# Copy to ~/.config/circuitforge/llm.yaml (shared across all CF products)
# or to config/llm.yaml (Kiwi-local, takes precedence).
#
# Kiwi uses LLMs for:
# - Expiry prediction fallback (unknown products not in the lookup table)
# - Meal planning suggestions
#
# Local inference (Ollama / vLLM) is the default path — no API key required.
# BYOK (bring your own key): set api_key_env to point at your API key env var.
# cf-orch trunk: set CF_ORCH_URL env var to allocate cf-text on-demand via
# the coordinator instead of hitting a static URL.
backends:
ollama:
type: openai_compat
enabled: true
base_url: http://localhost:11434/v1
model: llama3.2:3b
api_key: ollama
supports_images: false
vllm:
type: openai_compat
enabled: false
base_url: http://localhost:8000/v1
model: __auto__ # resolved from /v1/models at runtime
api_key: ''
supports_images: false
# ── cf-orch trunk services ──────────────────────────────────────────────────
# These allocate via cf-orch rather than connecting to a static URL.
# cf-orch starts the service on-demand and returns its live URL.
# Set CF_ORCH_URL env var or fill in url below; leave enabled: false if
# cf-orch is not deployed in your environment.
cf_text:
type: openai_compat
enabled: false
base_url: http://localhost:8008/v1 # fallback when cf-orch is not available
model: __auto__
api_key: any
supports_images: false
cf_orch:
service: cf-text
# model_candidates: leave empty to use the service's default_model,
# or specify a catalog alias (e.g. "qwen2.5-3b").
model_candidates: []
ttl_s: 3600
# ── Cloud / BYOK ───────────────────────────────────────────────────────────
anthropic:
type: anthropic
enabled: false
model: claude-haiku-4-5-20251001
api_key_env: ANTHROPIC_API_KEY
supports_images: false
openai:
type: openai_compat
enabled: false
base_url: https://api.openai.com/v1
model: gpt-4o-mini
api_key_env: OPENAI_API_KEY
supports_images: false
fallback_order:
- cf_text
- ollama
- vllm
- anthropic
- openai

View file

@ -8,10 +8,8 @@ server {
# Proxy API requests to the FastAPI container via Docker bridge network.
location /api/ {
proxy_pass http://api:8512;
proxy_set_header Host $http_host;
# Prefer X-Real-IP set by Caddy (real client address); fall back to $remote_addr
# when accessed directly on LAN without Caddy in the path.
proxy_set_header X-Real-IP $http_x_real_ip;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $http_x_forwarded_proto;
# Forward the session header injected by Caddy from cf_session cookie.
@ -20,22 +18,6 @@ server {
client_max_body_size 20m;
}
# Direct-port LAN access (localhost:8515): when VITE_API_BASE='/kiwi', the frontend
# builds API calls as /kiwi/api/v1/... — proxy these to the API container.
# Through Caddy the /kiwi prefix is stripped before reaching nginx, so this block
# is only active for direct-port access without Caddy in the path.
# Longer prefix (/kiwi/api/ = 10 chars) beats ^~/kiwi/ (6 chars) per nginx rules.
location /kiwi/api/ {
rewrite ^/kiwi(/api/.*)$ $1 break;
proxy_pass http://api:8512;
proxy_set_header Host $http_host;
proxy_set_header X-Real-IP $http_x_real_ip;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $http_x_forwarded_proto;
proxy_set_header X-CF-Session $http_x_cf_session;
client_max_body_size 20m;
}
# When accessed directly (localhost:8515) instead of via Caddy (/kiwi path-strip),
# Vite's /kiwi base URL means assets are requested at /kiwi/assets/... but stored
# at /assets/... in nginx's root. Alias /kiwi/ → root so direct port access works.

View file

@ -1,69 +0,0 @@
# Installation
Kiwi runs as a Docker Compose stack: a FastAPI backend and a Vue 3 frontend served by nginx. No external services are required for the core feature set.
## Prerequisites
- Docker and Docker Compose
- 500 MB disk for images + space for your pantry database
## Quick setup
```bash
git clone https://git.opensourcesolarpunk.com/Circuit-Forge/kiwi
cd kiwi
cp .env.example .env
./manage.sh build
./manage.sh start
```
The web UI opens at `http://localhost:8511`. The FastAPI backend is at `http://localhost:8512`.
## manage.sh commands
| Command | Description |
|---------|-------------|
| `./manage.sh start` | Start all services |
| `./manage.sh stop` | Stop all services |
| `./manage.sh restart` | Restart all services |
| `./manage.sh status` | Show running containers |
| `./manage.sh logs` | Tail logs (all services) |
| `./manage.sh build` | Rebuild images |
| `./manage.sh open` | Open browser to the web UI |
## Environment variables
Copy `.env.example` to `.env` and configure:
```bash
# Required — generate a random secret
SECRET_KEY=your-random-secret-here
# Optional — LLM backend for AI features (receipt OCR, recipe suggestions)
# See LLM Setup guide for details
LLM_BACKEND=ollama # ollama | openai-compatible | vllm
LLM_BASE_URL=http://localhost:11434
LLM_MODEL=llama3.1
```
## Data location
By default, Kiwi stores its SQLite database in `./data/kiwi.db` inside the repo directory. The `data/` folder is bind-mounted into the container so your pantry survives image rebuilds.
## Updating
```bash
git pull
./manage.sh build
./manage.sh restart
```
Database migrations run automatically on startup.
## Uninstalling
```bash
./manage.sh stop
docker compose down -v # removes containers and volumes
rm -rf data/ # removes local database
```

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@ -1,74 +0,0 @@
# LLM Backend Setup (Optional)
An LLM backend unlocks **receipt OCR**, **recipe suggestions (L3L4)**, and **style auto-classification**. Everything else works without one.
You can use any OpenAI-compatible inference server: Ollama, vLLM, LM Studio, a local llama.cpp server, or a commercial API.
## BYOK — Bring Your Own Key
BYOK means you provide your own LLM backend. Paid AI features are unlocked at **any tier** when a valid backend is configured. You pay for your own inference; Kiwi just uses it.
## Choosing a backend
| Backend | Best for | Notes |
|---------|----------|-------|
| **Ollama** | Local, easy setup | Recommended for getting started |
| **vLLM** | Local, high throughput | Better for faster hardware |
| **OpenAI API** | No local GPU | Requires paid API key |
| **Anthropic API** | No local GPU | Requires paid API key |
## Ollama setup (recommended)
```bash
# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh
# Pull a model — llama3.1 8B works well for recipe tasks
ollama pull llama3.1
# Verify it's running
ollama list
```
In your Kiwi `.env`:
```bash
LLM_BACKEND=ollama
LLM_BASE_URL=http://host.docker.internal:11434
LLM_MODEL=llama3.1
```
!!! note "Docker networking"
Use `host.docker.internal` instead of `localhost` when Ollama is running on your host and Kiwi is in Docker.
## OpenAI-compatible API
```bash
LLM_BACKEND=openai
LLM_BASE_URL=https://api.openai.com/v1
LLM_API_KEY=sk-your-key-here
LLM_MODEL=gpt-4o-mini
```
## Verify the connection
In the Kiwi **Settings** page, the LLM status indicator shows whether the backend is reachable. A green checkmark means OCR and L3L4 recipe suggestions are active.
## What LLM is used for
| Feature | LLM required |
|---------|-------------|
| Receipt OCR (line-item extraction) | Yes |
| Recipe suggestions L1 (pantry match) | No |
| Recipe suggestions L2 (substitution) | No |
| Recipe suggestions L3 (style templates) | Yes |
| Recipe suggestions L4 (full generation) | Yes |
| Style auto-classifier | Yes |
L1 and L2 suggestions use deterministic matching — they work without any LLM configured. See [Recipe Engine](../reference/recipe-engine.md) for the full algorithm breakdown.
## Model recommendations
- **Receipt OCR**: any model with vision capability (LLaVA, GPT-4o, etc.)
- **Recipe suggestions**: 7B13B instruction-tuned models work well; larger models produce more creative L4 output
- **Style classification**: small models handle this fine (3B+)

View file

@ -1,52 +0,0 @@
# Quick Start
This guide walks you through adding your first pantry item and getting a recipe suggestion. No LLM backend needed for these steps.
## 1. Add an item by barcode
Open the **Inventory** tab. Tap the barcode icon or click **Scan barcode**, then point your camera at a product barcode. Kiwi looks up the product in the open barcode database and adds it to your pantry.
If the barcode isn't recognized, you'll be prompted to enter the product name and details manually.
## 2. Add an item manually
Click **Add item** and fill in:
- **Name** — what is it? (e.g., "Canned chickpeas")
- **Quantity** — how many or how much
- **Expiry date** — when does it expire? (optional but recommended)
- **Category** — used for dietary filtering and pantry stats
## 3. Upload a receipt
Click **Receipts** in the sidebar, then **Upload receipt**. Take a photo of a grocery receipt or upload an image from your device.
- **Free tier**: the receipt is stored for you to review; line items are entered manually
- **Paid / BYOK**: OCR runs automatically and extracts items for you to approve
## 4. Browse recipes
Click **Recipes** in the sidebar. The recipe browser shows your **pantry match percentage** for each recipe — how much of the ingredient list you already have.
Use the filters to narrow by:
- **Cuisine** — Italian, Mexican, Japanese, etc.
- **Meal type** — breakfast, lunch, dinner, snack
- **Dietary** — vegetarian, vegan, gluten-free, dairy-free, etc.
- **Main ingredient** — chicken, pasta, lentils, etc.
## 5. Get a suggestion based on what's expiring
Click **Leftover mode** (the clock icon or toggle). Kiwi re-ranks suggestions to surface recipes that use your nearly-expired items first.
Free accounts get 5 leftover-mode requests per day. Paid accounts get unlimited.
## 6. Save a recipe
Click the bookmark icon on any recipe card to save it. You can add:
- **Notes** — cooking tips, modifications, family preferences
- **Star rating** — 0 to 5 stars
- **Style tags** — quick, comforting, weeknight, etc.
Saved recipes appear in the **Saved** tab. Paid accounts can organize them into named collections.

View file

@ -1,35 +0,0 @@
# Kiwi — Pantry Tracker
**Stop throwing food away. Cook what you already have.**
Kiwi tracks your pantry, watches for expiry dates, and suggests recipes based on what's about to go bad. Scan barcodes, photograph receipts, and let Kiwi tell you what to make for dinner — without needing an AI backend to do it.
![Kiwi pantry view](screenshots/01-pantry.png)
---
## What Kiwi does
- **Inventory tracking** — add items by barcode scan, receipt photo, or manual entry
- **Expiry alerts** — know what's about to go bad before it does
- **Recipe browser** — browse by cuisine, meal type, dietary preference, or main ingredient; see pantry match percentage inline
- **Leftover mode** — prioritize nearly-expired items when getting recipe suggestions
- **Receipt OCR** — extract line items from receipt photos automatically (Paid / BYOK)
- **Recipe suggestions** — four levels from pantry-match corpus to full LLM generation (Paid / BYOK)
- **Saved recipes** — bookmark any recipe with notes, 05 star rating, and style tags
- **CSV export** — export your full pantry inventory anytime
## Quick links
- [Installation](getting-started/installation.md) — local self-hosted setup
- [Quick Start](getting-started/quick-start.md) — add your first item and get a recipe
- [LLM Setup](getting-started/llm-setup.md) — unlock AI features with your own backend
- [Tier System](reference/tier-system.md) — what's free vs. paid
## No AI required
Inventory tracking, barcode scanning, expiry alerts, the recipe browser, saved recipes, and CSV export all work without any LLM configured. AI features (receipt OCR, recipe suggestions, style auto-classification) are optional and BYOK-unlockable at any tier.
## Free and open core
Discovery and pipeline code is MIT-licensed. AI features are BSL 1.1 — free for personal non-commercial self-hosting, commercial SaaS requires a license. See the [tier table](reference/tier-system.md) for the full breakdown.

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@ -1 +0,0 @@
(function(){var s=document.createElement("script");s.defer=true;s.dataset.domain="docs.circuitforge.tech,circuitforge.tech";s.dataset.api="https://analytics.circuitforge.tech/api/event";s.src="https://analytics.circuitforge.tech/js/script.js";document.head.appendChild(s);})();

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@ -1,80 +0,0 @@
# Architecture
Kiwi is a self-contained Docker Compose stack with a Vue 3 (SPA) frontend and a FastAPI backend backed by SQLite.
## Stack
| Layer | Technology |
|-------|-----------|
| Frontend | Vue 3 + TypeScript + Vite |
| Backend | FastAPI (Python 3.11+) |
| Database | SQLite (via circuitforge-core) |
| Auth (cloud) | CF session cookie → Directus JWT |
| Licensing | Heimdall (RS256 JWT, offline-capable) |
| LLM inference | Pluggable — Ollama, vLLM, OpenAI-compatible |
| Barcode lookup | Open Food Facts / UPC Database API |
| OCR | LLM vision model (configurable) |
## Data flow
```mermaid
graph LR
User -->|browser| Vue3[Vue 3 SPA]
Vue3 -->|/api/*| FastAPI
FastAPI -->|SQL| SQLite[(SQLite DB)]
FastAPI -->|HTTP| LLM[LLM Backend]
FastAPI -->|HTTP| Barcode[Barcode DB API]
FastAPI -->|JWT| Heimdall[Heimdall License]
```
## Docker Compose services
```yaml
services:
api:
# FastAPI backend — network_mode: host in dev
# Exposed at port 8512
web:
# Vue 3 SPA served by nginx
# Exposed at port 8511
```
In development, the API uses host networking so nginx can reach it at `172.17.0.1:8512` (Docker bridge gateway).
## Database
SQLite at `./data/kiwi.db`. The schema is managed by numbered migration files in `app/db/migrations/`. Migrations run automatically on startup — the startup script applies any new `*.sql` files in order.
Key tables:
| Table | Purpose |
|-------|---------|
| `products` | Product catalog (shared, barcode-keyed) |
| `pantry_items` | User's pantry (quantity, expiry, notes) |
| `recipes` | Recipe corpus |
| `saved_recipes` | User-bookmarked recipes |
| `collections` | Named recipe collections (Paid) |
| `receipts` | Receipt uploads and OCR results |
| `user_preferences` | User settings (dietary, LLM config) |
## Cloud mode
In cloud mode (managed instance at `menagerie.circuitforge.tech/kiwi`), each user gets their own SQLite database isolated under `/devl/kiwi-cloud-data/<user_id>/kiwi.db`. The cloud compose stack adds:
- `CLOUD_MODE=true` environment variable
- Directus JWT validation for session resolution
- Heimdall tier check on AI feature endpoints
The same codebase runs in both local and cloud modes — the cloud session middleware is a thin wrapper around the local auth logic.
## LLM integration
Kiwi uses `circuitforge-core`'s LLM router, which abstracts over Ollama, vLLM, and OpenAI-compatible APIs. The router is configured via environment variables at startup. All LLM calls are asynchronous and non-blocking — if the backend is unavailable, Kiwi falls back to the highest deterministic level (L2) and returns results without waiting.
## Privacy
- No PII is logged in production
- Pantry data stays on your machine in self-hosted mode
- Cloud mode: data stored per-user on Heimdall server, not shared with third parties, not used for training
- LLM calls include pantry context in the prompt — if using a cloud API, that context leaves your machine
- Using a local LLM backend (Ollama, vLLM) keeps all data on-device

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@ -1,75 +0,0 @@
# Recipe Engine
Kiwi uses a four-level recipe suggestion system. Each level adds more intelligence and better results, but requires more resources. Levels 12 are fully deterministic and work without any LLM. Levels 34 require an LLM backend.
## Level overview
| Level | Name | LLM required | Description |
|-------|------|-------------|-------------|
| L1 | Pantry match | No | Rank existing corpus by ingredient overlap |
| L2 | Substitution | No | Suggest swaps for missing ingredients |
| L3 | Style templates | Yes | Generate recipe variations from style templates |
| L4 | Full generation | Yes | Generate new recipes from scratch |
## L1 — Pantry match
The simplest level. Kiwi scores every recipe in the corpus by how many of its ingredients you already have:
```
score = (matched ingredients) / (total ingredients)
```
Recipes are sorted by this score descending. If leftover mode is active, the score is further weighted by expiry proximity.
This works entirely offline with no LLM — just set arithmetic on your current pantry.
## L2 — Substitution
L2 extends L1 by suggesting substitutions for missing ingredients. When a recipe scores well but you're missing one or two items, Kiwi checks a substitution table to see if something in your pantry could stand in:
- Buttermilk → plain yogurt + lemon juice
- Heavy cream → evaporated milk
- Fresh herbs → dried herbs (adjusted quantity)
Substitutions are sourced from a curated table — no LLM involved. L2 raises the effective match score for recipes where a reasonable substitute exists.
## L3 — Style templates
L3 uses the LLM to generate recipe variations from a style template. Rather than generating fully free-form text, it fills in a structured template:
```
[protein] + [vegetable] + [starch] + [sauce/flavor profile]
```
The template is populated from your pantry contents and the style tags you've set (e.g., "quick", "Italian"). The LLM fills in the techniques, proportions, and instructions.
Style templates produce consistent, practical results with less hallucination risk than fully open-ended generation.
## L4 — Full generation
L4 gives the LLM full creative freedom. Kiwi passes:
- Your full pantry inventory
- Your dietary preferences
- Any expiring items (if leftover mode is active)
- Your saved recipe history and style tags
The LLM generates a new recipe optimized for your situation. Results are more creative than L1L3 but require a capable model (7B+ recommended) and take longer to generate.
## Escalation
When you click **Suggest**, Kiwi tries each level in order and returns results as soon as a level produces usable output:
1. L1 and L2 run immediately (no LLM)
2. If no good matches exist (all scores < 30%), Kiwi escalates to L3
3. If L3 produces no results (LLM unavailable or error), Kiwi falls back to best L1 result
4. L4 is only triggered explicitly by the user ("Generate something new")
## Tier gates
| Level | Free | Paid | BYOK (any tier) |
|-------|------|------|-----------------|
| L1 — Pantry match | ✓ | ✓ | ✓ |
| L2 — Substitution | ✓ | ✓ | ✓ |
| L3 — Style templates | — | ✓ | ✓ |
| L4 — Full generation | — | ✓ | ✓ |

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@ -1,53 +0,0 @@
# Tier System
Kiwi uses CircuitForge's standard four-tier model. The free tier covers the full pantry tracking workflow. AI features are gated behind Paid or BYOK.
## Feature matrix
| Feature | Free | Paid | Premium |
|---------|------|------|---------|
| **Inventory** | | | |
| Inventory CRUD | ✓ | ✓ | ✓ |
| Barcode scan | ✓ | ✓ | ✓ |
| Receipt upload | ✓ | ✓ | ✓ |
| Expiry alerts | ✓ | ✓ | ✓ |
| CSV export | ✓ | ✓ | ✓ |
| **Recipes** | | | |
| Recipe browser | ✓ | ✓ | ✓ |
| Pantry match (L1) | ✓ | ✓ | ✓ |
| Substitution (L2) | ✓ | ✓ | ✓ |
| Style templates (L3) | BYOK | ✓ | ✓ |
| Full generation (L4) | BYOK | ✓ | ✓ |
| Leftover mode | 5/day | Unlimited | Unlimited |
| **Saved recipes** | | | |
| Save + notes + star rating | ✓ | ✓ | ✓ |
| Style tags (manual) | ✓ | ✓ | ✓ |
| LLM style auto-classifier | — | BYOK | ✓ |
| Named collections | — | ✓ | ✓ |
| Meal planning | — | ✓ | ✓ |
| **OCR** | | | |
| Receipt OCR | BYOK | ✓ | ✓ |
| **Account** | | | |
| Multi-household | — | — | ✓ |
**BYOK** = Bring Your Own LLM backend. Configure a local or cloud inference endpoint and these features activate at any tier. See [LLM Setup](../getting-started/llm-setup.md).
## Pricing
| Tier | Monthly | Lifetime |
|------|---------|----------|
| Free | $0 | — |
| Paid | $8/mo | $129 |
| Premium | $16/mo | $249 |
Lifetime licenses are available at [circuitforge.tech](https://circuitforge.tech).
## Self-hosting
Self-hosted Kiwi is free under the MIT license (inventory/pipeline) and BSL 1.1 (AI features, free for personal non-commercial use). You run it on your own hardware with your own LLM backend. No subscription required.
The cloud-managed instance at `menagerie.circuitforge.tech/kiwi` runs the same codebase and requires a CircuitForge account.
## Free key
Claim a free Paid-tier key (30 days) at [circuitforge.tech](https://circuitforge.tech/free-key). No credit card required.

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# Barcode Scanning
Kiwi's barcode scanner uses your device camera to look up products instantly. It works for UPC-A, UPC-E, EAN-13, EAN-8, and QR codes on packaged foods.
## How to scan
1. Open the **Inventory** tab
2. Click the **Scan barcode** button (camera icon)
3. Hold the barcode in the camera frame
4. Kiwi decodes it and looks up the product
## What happens after a scan
**Product found in database:**
Kiwi fills in the product name, category, and any nutritional metadata from the open barcode database. You confirm the quantity and expiry date, then save.
**Product not found:**
You'll see a manual entry form with the raw barcode pre-filled. Add a name and the product is saved to your personal pantry (not contributed to the shared database).
## Supported formats
| Format | Common use |
|--------|-----------|
| UPC-A (12 digit) | US grocery products |
| EAN-13 (13 digit) | International grocery products |
| UPC-E (compressed) | Small packaging |
| EAN-8 | Small packaging |
| QR Code | Some specialty products |
## Tips for reliable scanning
- **Good lighting**: scanning works best in well-lit conditions
- **Steady hand**: hold the camera still for 12 seconds
- **Fill the frame**: bring the barcode close enough to fill most of the camera view
- **Flat surface**: wrinkled or curved barcodes are harder to decode
## Manual barcode entry
If camera scanning isn't available (browser permissions denied, no camera, etc.), you can type the barcode number directly into the **Barcode** field on the manual add form.

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@ -1,62 +0,0 @@
# Inventory
![Kiwi pantry view](../screenshots/01-pantry.png)
The inventory is your pantry. Every item you add gives Kiwi the data it needs to show pantry match percentages, flag expiry, and rank recipe suggestions.
## Adding items
### By barcode
Tap the barcode scanner icon. Point your camera at the barcode on the product. Kiwi checks the open barcode database and fills in the product name and category.
If the product isn't in the database, you'll see a manual entry form pre-filled with whatever was decoded from the barcode — just add a name and save.
### By receipt
Upload a receipt photo in the **Receipts** tab. After the receipt is processed, approved items are added to your pantry in bulk. See [Receipt OCR](receipt-ocr.md) for details.
### Manually
Click **Add item** and fill in:
| Field | Required | Notes |
|-------|----------|-------|
| Name | Yes | What is it? |
| Quantity | Yes | Number + unit (e.g., "2 cans", "500 g") |
| Expiry date | No | Used for expiry alerts and leftover mode |
| Category | No | Helps with dietary filtering |
| Notes | No | Storage instructions, opened date, etc. |
## Editing and deleting
Click any item in the list to edit its quantity, expiry date, or notes. Items can be deleted individually or in bulk via the selection checkbox.
## Expiry alerts
Kiwi flags items approaching expiry with a color indicator:
- **Red**: expires within 2 days
- **Orange**: expires within 7 days
- **Yellow**: expires within 14 days
The **Leftover mode** uses this same expiry window to prioritize nearly-expired items in recipe rankings.
## Inventory stats
The stats panel (top of the Inventory page) shows:
- Total items in pantry
- Items expiring this week
- Breakdown by category
- Items added this month
## CSV export
Click **Export** to download your full pantry as a CSV file. The export includes name, quantity, category, expiry date, and notes for every item.
## Bulk operations
- Select multiple items with the checkbox column
- **Delete selected** — remove items in bulk
- **Mark as used** — remove items you've cooked with (coming in Phase 3)

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@ -1,39 +0,0 @@
# Leftover Mode
![Kiwi recipe results with pantry match](../screenshots/03-recipe-results.png)
Leftover mode re-ranks recipe suggestions to surface dishes that use your nearly-expired items first. It's the fastest way to answer "what should I cook before this goes bad?"
## Activating leftover mode
Click the **clock icon** or the **Leftover mode** toggle in the recipe browser. The recipe list immediately re-sorts to prioritize recipes that use items expiring within the next 7 days.
## How it works
When leftover mode is active, Kiwi weights the pantry match score toward items closer to their expiry date. A recipe that uses your 3-day-old spinach and day-old mushrooms ranks higher than a recipe that only uses shelf-stable pantry staples — even if the pantry match percentage is similar.
Items without an expiry date set are not weighted for leftover mode purposes. Setting expiry dates when you add items makes leftover mode much more useful.
## Rate limits
| Tier | Leftover mode requests |
|------|----------------------|
| Free | 5 per day |
| Paid | Unlimited |
| Premium | Unlimited |
A "request" is each time you activate leftover mode or click **Refresh**. The re-sort count resets at midnight.
## What counts as "nearly expired"
The leftover mode window uses the same thresholds as the expiry indicators:
- **Expiring within 2 days** — highest priority
- **Expiring within 7 days** — elevated priority
- **Expiring within 14 days** — mildly elevated priority
Items past their expiry date are still included (Kiwi doesn't remove them automatically) but displayed with a red indicator. Use your judgment — some items are fine past date, others aren't.
## Combining with filters
Leftover mode stacks with the dietary and cuisine filters. You can activate leftover mode and filter by "Vegetarian" or "Under 30 minutes" to narrow down to recipes that both use expiring items and match your constraints.

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@ -1,57 +0,0 @@
# Receipt OCR
![Kiwi receipt upload](../screenshots/04-receipts.png)
Receipt OCR automatically extracts grocery line items from a photo of your receipt and adds them to your pantry after you approve. It's available on the Paid tier and BYOK-unlockable on Free.
## Upload a receipt
1. Click **Receipts** in the sidebar
2. Click **Upload receipt**
3. Take a photo or select an image from your device
Supported formats: JPEG, PNG, HEIC, WebP. Maximum file size: 10 MB.
## How OCR processing works
When a receipt is uploaded:
1. **OCR runs** — the LLM reads the receipt image and identifies line items, quantities, and prices
2. **Review screen** — you see each extracted item with its detected quantity
3. **Approve or edit** — correct any mistakes, remove items you don't want tracked
4. **Confirm** — approved items are added to your pantry in bulk
The whole flow is designed around human approval — Kiwi never silently adds items to your pantry. You always see what's being imported and can adjust before confirming.
## Reviewing extracted items
Each extracted line item shows:
- **Product name** — as extracted from the receipt
- **Quantity** — detected from the receipt text (e.g., "2 × Canned Tomatoes")
- **Confidence** — how certain the OCR is about this item
- **Edit** — correct the name or quantity inline
- **Remove** — exclude this item from the import
Low-confidence items are flagged with a yellow indicator. Review those carefully — store abbreviations and handwriting can trip up the extractor.
## Free tier behavior
On the Free tier without a BYOK backend configured:
- Receipts are stored and displayed
- OCR does **not** run automatically
- You can enter items from the receipt manually using the item list view
To enable automatic OCR on Free tier, configure a [BYOK LLM backend](../getting-started/llm-setup.md).
## Tips for better results
- **Flatten the receipt**: lay it on a flat surface rather than crumpling
- **Include the full receipt**: get all four edges in frame
- **Good lighting**: avoid glare on thermal paper
- **Fresh receipts**: faded thermal receipts (older than a few months) are harder to read
## Re-running OCR
If OCR produced poor results, you can trigger a re-run from the receipt detail view. Each re-run uses a fresh extraction — previous results are discarded.

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@ -1,50 +0,0 @@
# Recipe Browser
![Kiwi recipe finder](../screenshots/02-recipes.png)
The recipe browser lets you explore the full recipe corpus filtered by cuisine, meal type, dietary preference, and main ingredient. Your **pantry match percentage** is shown on every recipe card so you can see at a glance what you can cook tonight.
## Browsing by domain
The recipe corpus is organized into three domains:
| Domain | Examples |
|--------|---------|
| **Cuisine** | Italian, Mexican, Japanese, Indian, Mediterranean, West African, ... |
| **Meal type** | Breakfast, Lunch, Dinner, Snack, Dessert, Drink |
| **Dietary** | Vegetarian, Vegan, Gluten-free, Dairy-free, Low-carb, Nut-free |
Click a domain tile to see its categories. Click a category to browse the recipes inside it.
## Pantry match percentage
Every recipe card shows what percentage of the ingredient list you already have in your pantry. This updates as your inventory changes.
- **100%**: you have everything — cook it now
- **7099%**: almost there, minor shopping needed
- **< 50%**: you'd need to buy most of the ingredients
## Filtering
Use the filter bar to narrow results:
- **Dietary** — show only recipes matching your dietary preferences
- **Min pantry match** — hide recipes below a match threshold
- **Time** — prep + cook time total
- **Sort** — by pantry match (default), alphabetical, or rating (for saved recipes)
## Recipe detail
Click any recipe card to open the full recipe:
- Ingredient list with **in pantry / not in pantry** indicators
- Step-by-step instructions
- Substitution suggestions for missing ingredients
- Nutritional summary
- **Bookmark** button to save with notes and rating
## Getting suggestions
The recipe browser shows the **full corpus** sorted by pantry match. For AI-powered suggestions tailored to what's expiring, use [Leftover Mode](leftover-mode.md) or the **Suggest** button (Paid / BYOK).
See [Recipe Engine](../reference/recipe-engine.md) for how the four suggestion levels work.

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@ -1,53 +0,0 @@
# Saved Recipes
Save any recipe from the browser to your personal collection. Add notes, a star rating, and style tags to build a library of recipes you love.
## Saving a recipe
Click the **bookmark icon** on any recipe card or the **Save** button in the recipe detail view. The recipe is immediately saved to your **Saved** tab.
## Notes and ratings
On each saved recipe you can add:
- **Notes** — your modifications, family feedback, what you'd change next time
- **Star rating** — 0 to 5 stars; used to sort your collection
- **Style tags** — free-text labels like "quick", "comforting", "weeknight", "meal prep"
Click the pencil icon on a saved recipe to edit these fields.
## Style tags
Style tags are free-text — type anything that helps you find the recipe later. Common tags used by Kiwi users:
`quick` · `weeknight` · `comforting` · `meal prep` · `kid-friendly` · `hands-off` · `summer` · `one-pot`
**Paid tier and above:** the LLM style auto-classifier can suggest tags based on the recipe's ingredients and instructions. Click **Auto-tag** on any saved recipe to get suggestions you can accept or dismiss.
## Collections (Paid)
On the Paid tier, you can organize saved recipes into named collections:
1. Click **New collection** in the Saved tab
2. Give it a name (e.g., "Weeknight dinners", "Holiday baking")
3. Add recipes to the collection from the saved recipe list or directly when saving
Collections are listed in the sidebar of the Saved tab. A recipe can belong to multiple collections.
## Sorting and filtering saved recipes
Sort by:
- **Date saved** (newest first, default)
- **Star rating** (highest first)
- **Pantry match** (how many ingredients you currently have)
- **Alphabetical**
Filter by:
- **Collection** (Paid)
- **Style tag**
- **Star rating** (e.g., show only 4+ star recipes)
- **Dietary**
## Removing a recipe
Click the bookmark icon again (or the **Remove** button in the detail view) to unsave a recipe. Your notes and rating are lost when you unsave — there's no archive.

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@ -1,63 +0,0 @@
# Settings
The Settings page lets you configure your LLM backend, dietary preferences, notification behavior, and account details.
## LLM backend
Shows the currently configured inference backend and its connection status. A green indicator means Kiwi can reach the backend and AI features are active. A red indicator means the backend is unreachable — check the URL and whether the server is running.
To change or add a backend, edit your `.env` file and restart:
```bash
LLM_BACKEND=ollama
LLM_BASE_URL=http://host.docker.internal:11434
LLM_MODEL=llama3.1
```
See [LLM Backend Setup](../getting-started/llm-setup.md) for full configuration options.
## Dietary preferences
Set your default dietary filters here. These are applied automatically when you browse recipes and get suggestions:
- Vegetarian
- Vegan
- Gluten-free
- Dairy-free
- Nut-free
- Low-carb
- Halal
- Kosher
Dietary preferences are stored locally and not shared with any server.
## Expiry alert thresholds
Configure when Kiwi starts flagging items:
| Indicator | Default |
|-----------|---------|
| Red (urgent) | 2 days |
| Orange (soon) | 7 days |
| Yellow (upcoming) | 14 days |
## Notification settings
Kiwi can send browser notifications when items are about to expire. Enable this in Settings by clicking **Allow notifications**. Your browser will ask for permission.
Notifications are sent once per day for items entering the red (2-day) window.
## Account and tier
Shows your current tier (Free / Paid / Premium) and account email (cloud mode only). Includes a link to manage your subscription.
## Affiliate links
When browsing recipes that call for specialty ingredients, Kiwi may show eBay links to find them at a discount. You can:
- **Disable affiliate links entirely** — turn off all affiliate link insertion
- **Use your own affiliate ID** — if you have an eBay Partner Network (EPN) ID, enter it here and your ID will be used instead of CircuitForge's (Premium tier)
## Export
Click **Export pantry** to download your full inventory as a CSV file. The export includes all items, quantities, categories, expiry dates, and notes.

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@ -23,9 +23,6 @@
.app-body { display: flex; flex-direction: column; flex: 1; }
}
</style>
<!-- Plausible analytics: cookie-free, GDPR-compliant, self-hosted.
Skips localhost/127.0.0.1. Reports to hostname + circuitforge.tech rollup. -->
<script>(function(){if(/localhost|127\.0\.0\.1/.test(location.hostname))return;var s=document.createElement('script');s.defer=true;s.dataset.domain=location.hostname+',circuitforge.tech';s.dataset.api='https://analytics.circuitforge.tech/api/event';s.src='https://analytics.circuitforge.tech/js/script.js';document.head.appendChild(s);})();</script>
</head>
<body>
<div id="app"></div>

View file

@ -58,15 +58,6 @@
<span class="sidebar-label">Meal Plan</span>
</button>
<button :class="['sidebar-item', { active: currentTab === 'shopping' }]" @click="switchTab('shopping')" aria-label="Shopping List">
<svg class="nav-icon" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true">
<path d="M6 2L3 6v14a2 2 0 002 2h14a2 2 0 002-2V6l-3-4z"/>
<line x1="3" y1="6" x2="21" y2="6"/>
<path d="M16 10a4 4 0 01-8 0"/>
</svg>
<span class="sidebar-label">Shopping</span>
</button>
<button :class="['sidebar-item', { active: currentTab === 'settings' }]" @click="switchTab('settings')">
<svg class="nav-icon" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round">
<circle cx="12" cy="12" r="3"/>
@ -88,24 +79,21 @@
<main class="app-main">
<div class="container">
<div v-if="mountedTabs.has('inventory')" v-show="currentTab === 'inventory'" class="tab-content fade-in">
<div v-show="currentTab === 'inventory'" class="tab-content fade-in">
<InventoryList />
</div>
<div v-if="mountedTabs.has('receipts')" v-show="currentTab === 'receipts'" class="tab-content fade-in">
<div v-show="currentTab === 'receipts'" class="tab-content fade-in">
<ReceiptsView />
</div>
<div v-show="currentTab === 'recipes'" class="tab-content fade-in">
<RecipesView />
</div>
<div v-if="mountedTabs.has('settings')" v-show="currentTab === 'settings'" class="tab-content fade-in">
<div v-show="currentTab === 'settings'" class="tab-content fade-in">
<SettingsView />
</div>
<div v-if="mountedTabs.has('mealplan')" v-show="currentTab === 'mealplan'" class="tab-content">
<div v-show="currentTab === 'mealplan'" class="tab-content">
<MealPlanView />
</div>
<div v-if="mountedTabs.has('shopping')" v-show="currentTab === 'shopping'" class="tab-content fade-in">
<ShoppingView />
</div>
</div>
</main>
</div>
@ -156,14 +144,6 @@
</svg>
<span class="nav-label">Meal Plan</span>
</button>
<button :class="['nav-item', { active: currentTab === 'shopping' }]" @click="switchTab('shopping')" aria-label="Shopping List">
<svg class="nav-icon" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true">
<path d="M6 2L3 6v14a2 2 0 002 2h14a2 2 0 002-2V6l-3-4z"/>
<line x1="3" y1="6" x2="21" y2="6"/>
<path d="M16 10a4 4 0 01-8 0"/>
</svg>
<span class="nav-label">Shopping</span>
</button>
</nav>
<!-- Feedback FAB hidden when FORGEJO_API_TOKEN not configured -->
@ -204,26 +184,21 @@
</template>
<script setup lang="ts">
import { ref, reactive, onMounted } from 'vue'
import { ref, onMounted } from 'vue'
import InventoryList from './components/InventoryList.vue'
import ReceiptsView from './components/ReceiptsView.vue'
import RecipesView from './components/RecipesView.vue'
import SettingsView from './components/SettingsView.vue'
import MealPlanView from './components/MealPlanView.vue'
import ShoppingView from './components/ShoppingView.vue'
import FeedbackButton from './components/FeedbackButton.vue'
import { useInventoryStore } from './stores/inventory'
import { useEasterEggs } from './composables/useEasterEggs'
import { householdAPI, bootstrapSession } from './services/api'
import { householdAPI } from './services/api'
type Tab = 'inventory' | 'receipts' | 'recipes' | 'settings' | 'mealplan' | 'shopping'
type Tab = 'inventory' | 'receipts' | 'recipes' | 'settings' | 'mealplan'
const currentTab = ref<Tab>('recipes')
const currentTab = ref<Tab>('inventory')
const sidebarCollapsed = ref(false)
// Lazy-mount: tabs mount on first visit and stay mounted (KeepAlive-like behaviour).
// Only 'recipes' is in the initial set so non-active tabs don't mount simultaneously
// on page load eliminates concurrent onMounted calls across all tab components.
const mountedTabs = reactive(new Set<Tab>(['recipes']))
const inventoryStore = useInventoryStore()
const { kiwiVisible, kiwiDirection } = useEasterEggs()
@ -243,7 +218,6 @@ function onWordmarkClick() {
}
async function switchTab(tab: Tab) {
mountedTabs.add(tab)
currentTab.value = tab
if (tab === 'recipes' && inventoryStore.items.length === 0) {
await inventoryStore.fetchItems()
@ -251,15 +225,6 @@ async function switchTab(tab: Tab) {
}
onMounted(async () => {
// Session bootstrap logs auth= + tier= server-side for log-based analytics.
// Fire-and-forget: failure doesn't affect UX.
bootstrapSession()
// Pre-fetch inventory so Recipes tab has data on first load
if (inventoryStore.items.length === 0) {
await inventoryStore.fetchItems()
}
// Handle household invite links: /#/join?household_id=xxx&token=yyy
const hash = window.location.hash
if (hash.includes('/join')) {

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@ -1,275 +0,0 @@
<template>
<Transition name="modal">
<div v-if="show" class="modal-overlay" @click="handleCancel">
<div class="modal-container" @click.stop>
<div class="modal-header">
<h3>{{ title }}</h3>
</div>
<div class="modal-body">
<p>{{ message }}</p>
<!-- Partial quantity input -->
<div v-if="inputType === 'quantity'" class="action-input-row">
<label class="action-input-label">{{ inputLabel }}</label>
<div class="qty-input-group">
<input
v-model.number="inputNumber"
type="number"
:min="0.01"
:max="inputMax"
step="0.5"
class="action-number-input"
:aria-label="inputLabel"
/>
<span class="qty-unit">{{ inputUnit }}</span>
</div>
<button class="btn-use-all" @click="inputNumber = inputMax">
Use all ({{ inputMax }} {{ inputUnit }})
</button>
</div>
<!-- Reason select -->
<div v-if="inputType === 'select'" class="action-input-row">
<label class="action-input-label">{{ inputLabel }}</label>
<select v-model="inputSelect" class="action-select" :aria-label="inputLabel">
<option value=""> skip </option>
<option v-for="opt in inputOptions" :key="opt" :value="opt">{{ opt }}</option>
</select>
</div>
</div>
<div class="modal-footer">
<button class="btn btn-secondary" @click="handleCancel">Cancel</button>
<button :class="['btn', `btn-${type}`]" @click="handleConfirm">
{{ confirmText }}
</button>
</div>
</div>
</div>
</Transition>
</template>
<script setup lang="ts">
import { ref, watch } from 'vue'
interface Props {
show: boolean
title?: string
message: string
confirmText?: string
type?: 'primary' | 'danger' | 'warning' | 'secondary'
inputType?: 'quantity' | 'select' | null
inputLabel?: string
inputMax?: number
inputUnit?: string
inputOptions?: string[]
}
const props = withDefaults(defineProps<Props>(), {
title: 'Confirm',
confirmText: 'Confirm',
type: 'primary',
inputType: null,
inputLabel: '',
inputMax: 1,
inputUnit: '',
inputOptions: () => [],
})
const emit = defineEmits<{
confirm: [value: number | string | undefined]
cancel: []
}>()
const inputNumber = ref<number>(props.inputMax)
const inputSelect = ref<string>('')
watch(() => props.inputMax, (v) => { inputNumber.value = v })
watch(() => props.show, (v) => {
if (v) {
inputNumber.value = props.inputMax
inputSelect.value = ''
}
})
function handleConfirm() {
if (props.inputType === 'quantity') {
const qty = Math.min(Math.max(0.01, inputNumber.value || props.inputMax), props.inputMax)
emit('confirm', qty)
} else if (props.inputType === 'select') {
emit('confirm', inputSelect.value || undefined)
} else {
emit('confirm', undefined)
}
}
function handleCancel() {
emit('cancel')
}
</script>
<style scoped>
.modal-overlay {
position: fixed;
inset: 0;
background: rgba(0, 0, 0, 0.5);
display: flex;
align-items: center;
justify-content: center;
z-index: 9999;
padding: var(--spacing-lg);
}
.modal-container {
background: var(--color-bg-elevated);
border: 1px solid var(--color-border);
border-radius: var(--radius-xl);
box-shadow: var(--shadow-xl);
max-width: 480px;
width: 100%;
overflow: hidden;
}
.modal-header {
padding: var(--spacing-lg);
border-bottom: 1px solid var(--color-border);
}
.modal-header h3 {
margin: 0;
color: var(--color-text-primary);
font-size: var(--font-size-lg);
font-weight: 600;
}
.modal-body {
padding: var(--spacing-lg);
display: flex;
flex-direction: column;
gap: var(--spacing-md);
}
.modal-body p {
margin: 0;
color: var(--color-text-primary);
font-size: var(--font-size-base);
line-height: 1.5;
}
.action-input-row {
display: flex;
flex-direction: column;
gap: var(--spacing-xs);
}
.action-input-label {
font-size: var(--font-size-sm);
color: var(--color-text-secondary);
font-weight: 500;
}
.qty-input-group {
display: flex;
align-items: center;
gap: var(--spacing-sm);
}
.action-number-input {
width: 90px;
padding: var(--spacing-xs) var(--spacing-sm);
border: 1px solid var(--color-border);
border-radius: var(--radius-md);
background: var(--color-bg-primary);
color: var(--color-text-primary);
font-size: var(--font-size-base);
}
.qty-unit {
font-size: var(--font-size-sm);
color: var(--color-text-secondary);
}
.btn-use-all {
align-self: flex-start;
background: none;
border: none;
color: var(--color-primary);
font-size: var(--font-size-sm);
cursor: pointer;
padding: 0;
text-decoration: underline;
}
.action-select {
padding: var(--spacing-xs) var(--spacing-sm);
border: 1px solid var(--color-border);
border-radius: var(--radius-md);
background: var(--color-bg-primary);
color: var(--color-text-primary);
font-size: var(--font-size-base);
width: 100%;
}
.modal-footer {
padding: var(--spacing-lg);
border-top: 1px solid var(--color-border);
display: flex;
justify-content: flex-end;
gap: var(--spacing-md);
}
.btn {
padding: var(--spacing-sm) var(--spacing-lg);
border: none;
border-radius: var(--radius-md);
font-size: var(--font-size-base);
font-weight: 500;
cursor: pointer;
transition: all 0.2s ease;
}
.btn-secondary {
background: var(--color-bg-secondary);
color: var(--color-text-primary);
border: 1px solid var(--color-border);
}
.btn-secondary:hover { background: var(--color-bg-primary); }
.btn-primary {
background: var(--gradient-primary);
color: white;
}
.btn-primary:hover {
opacity: 0.9;
transform: translateY(-1px);
box-shadow: var(--shadow-md);
}
.btn-danger {
background: var(--color-error);
color: white;
}
.btn-danger:hover {
background: var(--color-error-dark);
transform: translateY(-1px);
}
.btn-warning {
background: var(--color-warning);
color: white;
}
/* Animations */
.modal-enter-active,
.modal-leave-active { transition: opacity 0.3s ease; }
.modal-enter-active .modal-container,
.modal-leave-active .modal-container { transition: transform 0.3s ease; }
.modal-enter-from,
.modal-leave-to { opacity: 0; }
.modal-enter-from .modal-container,
.modal-leave-to .modal-container { transform: scale(0.9) translateY(-20px); }
</style>

View file

@ -1,586 +0,0 @@
<template>
<div class="byo-tab">
<!-- Step 0: Template grid -->
<div v-if="phase === 'select'" class="byo-section">
<h2 class="section-title text-xl mb-sm">Build Your Own Recipe</h2>
<p class="text-sm text-secondary mb-md">
Choose a style, then pick your ingredients one step at a time.
</p>
<div v-if="templatesLoading" class="text-secondary text-sm">Loading templates</div>
<div v-else-if="templatesError" role="alert" class="status-badge status-error mb-md">
{{ templatesError }}
</div>
<div v-else class="template-grid" role="list">
<button
v-for="tmpl in templates"
:key="tmpl.id"
class="template-card card"
role="listitem"
:aria-label="tmpl.title + ': ' + tmpl.descriptor"
@click="selectTemplate(tmpl)"
>
<span class="tmpl-icon" aria-hidden="true">{{ tmpl.icon }}</span>
<span class="tmpl-title">{{ tmpl.title }}</span>
<span class="tmpl-descriptor text-sm text-secondary">{{ tmpl.descriptor }}</span>
</button>
</div>
</div>
<!-- Step 1+: Ingredient wizard -->
<div v-else-if="phase === 'wizard'" class="byo-section">
<!-- Back + step counter -->
<div class="byo-nav mb-sm">
<button class="btn btn-sm btn-secondary" @click="goBack"> Back</button>
<span class="text-sm text-secondary step-counter">Step {{ wizardStep + 1 }} of {{ totalSteps }}</span>
</div>
<h2 class="section-title text-xl mb-xs">What's your {{ currentRole?.display }}?</h2>
<p v-if="currentRole?.hint" class="text-sm text-secondary mb-md">{{ currentRole.hint }}</p>
<!-- Missing ingredient mode toggle -->
<div class="mode-toggle mb-sm" role="radiogroup" aria-label="Missing ingredients">
<button
v-for="mode in missingModes"
:key="mode.value"
:class="['btn', 'btn-sm', recipesStore.missingIngredientMode === mode.value ? 'btn-primary' : 'btn-secondary']"
:aria-checked="recipesStore.missingIngredientMode === mode.value"
role="radio"
@click="recipesStore.missingIngredientMode = mode.value as any"
>{{ mode.label }}</button>
</div>
<!-- Filter row: text search or tag cloud -->
<div class="filter-row mb-sm">
<input
v-if="recipesStore.builderFilterMode === 'text'"
v-model="filterText"
class="form-input filter-input"
:placeholder="'Search ' + (currentRole?.display ?? 'ingredients') + '…'"
aria-label="Search ingredients"
/>
<div
v-else
class="tag-cloud"
role="group"
aria-label="Filter by tag"
>
<button
v-for="tag in candidates?.available_tags ?? []"
:key="tag"
:class="['btn', 'btn-sm', 'tag-chip', selectedTags.has(tag) ? 'tag-active' : '']"
:aria-pressed="selectedTags.has(tag)"
@click="toggleTag(tag)"
>{{ tag }}</button>
<span v-if="(candidates?.available_tags ?? []).length === 0" class="text-secondary text-sm">
No tags available for this ingredient set.
</span>
</div>
<button
class="btn btn-sm btn-secondary filter-mode-btn"
:aria-pressed="recipesStore.builderFilterMode === 'tags'"
:aria-label="recipesStore.builderFilterMode === 'text' ? 'Switch to tag filter' : 'Switch to text search'"
@click="recipesStore.builderFilterMode = recipesStore.builderFilterMode === 'text' ? 'tags' : 'text'"
>{{ recipesStore.builderFilterMode === 'text' ? '🏷️' : '🔍' }}</button>
</div>
<!-- Candidates loading / error -->
<div v-if="candidatesLoading" class="text-secondary text-sm mb-sm">Loading options</div>
<div v-else-if="candidatesError" role="alert" class="status-badge status-error mb-sm">
{{ candidatesError }}
</div>
<!-- Compatible candidates -->
<div v-if="filteredCompatible.length > 0" class="candidates-section mb-sm">
<p class="text-xs font-semibold text-secondary mb-xs" aria-hidden="true">Available</p>
<div class="ingredient-grid">
<button
v-for="item in filteredCompatible"
:key="item.name"
:class="['ingredient-card', 'btn', selectedInRole.has(item.name) ? 'ingredient-active' : '']"
:aria-pressed="selectedInRole.has(item.name)"
:aria-label="item.name + (item.in_pantry ? '' : ' — not in pantry')"
@click="toggleIngredient(item.name)"
>
<span class="ingredient-name">{{ item.name }}</span>
<span v-if="!item.in_pantry && recipesStore.missingIngredientMode === 'add-to-cart'"
class="cart-icon" aria-hidden="true">🛒</span>
</button>
</div>
</div>
<!-- Other candidates (greyed or add-to-cart mode only) -->
<template v-if="recipesStore.missingIngredientMode !== 'hidden' && filteredOther.length > 0">
<div class="candidates-separator text-xs text-secondary mb-xs">also works</div>
<div class="ingredient-grid ingredient-grid-other mb-sm">
<button
v-for="item in filteredOther"
:key="item.name"
:class="['ingredient-card', 'btn',
item.in_pantry ? '' : 'ingredient-missing',
selectedInRole.has(item.name) ? 'ingredient-active' : '']"
:aria-pressed="selectedInRole.has(item.name)"
:aria-label="item.name + (item.in_pantry ? '' : ' — not in pantry')"
:disabled="!item.in_pantry && recipesStore.missingIngredientMode === 'greyed'"
@click="item.in_pantry || recipesStore.missingIngredientMode !== 'greyed' ? toggleIngredient(item.name) : undefined"
>
<span class="ingredient-name">{{ item.name }}</span>
<span v-if="!item.in_pantry && recipesStore.missingIngredientMode === 'add-to-cart'"
class="cart-icon" aria-hidden="true">🛒</span>
</button>
</div>
</template>
<!-- No-match state: nothing compatible AND nothing visible in other section.
filteredOther items are hidden when mode is 'hidden', so check visibility too. -->
<template v-if="!candidatesLoading && !candidatesError && filteredCompatible.length === 0 && (filteredOther.length === 0 || recipesStore.missingIngredientMode === 'hidden')">
<!-- Custom freeform input: text filter with no matches offer "use anyway" -->
<div v-if="recipesStore.builderFilterMode === 'text' && filterText.trim().length > 0" class="custom-ingredient-prompt mb-sm">
<p class="text-sm text-secondary mb-xs">
No match for "{{ filterText.trim() }}" in your pantry.
</p>
<button class="btn btn-secondary" @click="useCustomIngredient">
Use "{{ filterText.trim() }}" anyway
</button>
</div>
<!-- No pantry items at all for this role -->
<p v-else class="text-sm text-secondary mb-sm">
Nothing in your pantry fits this role yet. You can skip it or
<button class="btn-link" @click="recipesStore.missingIngredientMode = 'greyed'">show options to add.</button>
</p>
</template>
<!-- Skip / Next -->
<div class="byo-actions">
<button
v-if="!currentRole?.required"
class="btn btn-secondary"
@click="advanceStep"
>Skip (optional)</button>
<button
v-else-if="currentRole?.required && selectedInRole.size === 0"
class="btn btn-secondary"
@click="advanceStep"
>I'll add this later</button>
<button
class="btn btn-primary"
:disabled="buildLoading"
@click="wizardStep < totalSteps - 1 ? advanceStep() : buildRecipe()"
>
{{ wizardStep < totalSteps - 1 ? 'Next →' : 'Build this recipe' }}
</button>
</div>
</div>
<!-- Result -->
<div v-else-if="phase === 'result'" class="byo-section">
<div v-if="buildLoading" class="text-secondary text-sm mb-md">Building your recipe</div>
<div v-else-if="buildError" role="alert" class="status-badge status-error mb-md">
{{ buildError }}
</div>
<template v-else-if="builtRecipe">
<RecipeDetailPanel
:recipe="builtRecipe"
:grocery-links="[]"
@close="phase = 'select'"
@cooked="phase = 'select'"
/>
<!-- Shopping list: items the user chose that aren't in their pantry -->
<div v-if="(builtRecipe.missing_ingredients ?? []).length > 0" class="cart-list card mb-sm">
<h3 class="text-sm font-semibold mb-xs">🛒 You'll need to pick up</h3>
<ul class="cart-items">
<li v-for="item in builtRecipe.missing_ingredients" :key="item" class="cart-item text-sm">{{ item }}</li>
</ul>
</div>
<div class="byo-actions mt-sm">
<button class="btn btn-secondary" @click="resetToTemplate">Try a different build</button>
<button class="btn btn-secondary" @click="phase = 'wizard'">Adjust ingredients</button>
</div>
</template>
</div>
</div>
</template>
<script setup lang="ts">
import { ref, computed, onMounted } from 'vue'
import { useRecipesStore } from '../stores/recipes'
import RecipeDetailPanel from './RecipeDetailPanel.vue'
import { recipesAPI, type AssemblyTemplateOut, type RoleCandidatesResponse, type RecipeSuggestion } from '../services/api'
const recipesStore = useRecipesStore()
type Phase = 'select' | 'wizard' | 'result'
const phase = ref<Phase>('select')
// Template grid state
const templates = ref<AssemblyTemplateOut[]>([])
const templatesLoading = ref(false)
const templatesError = ref<string | null>(null)
// Wizard state
const selectedTemplate = ref<AssemblyTemplateOut | null>(null)
const wizardStep = ref(0)
const roleOverrides = ref<Record<string, string[]>>({})
// Candidates for current step
const candidates = ref<RoleCandidatesResponse | null>(null)
const candidatesLoading = ref(false)
const candidatesError = ref<string | null>(null)
// Filter state (reset on step advance)
const filterText = ref('')
const selectedTags = ref<Set<string>>(new Set())
// Result state
const builtRecipe = ref<RecipeSuggestion | null>(null)
const buildLoading = ref(false)
const buildError = ref<string | null>(null)
// Shopping list is derived from builtRecipe.missing_ingredients (computed by backend)
const missingModes = [
{ label: 'Available only', value: 'hidden' },
{ label: 'Show missing', value: 'greyed' },
{ label: 'Add to cart', value: 'add-to-cart' },
]
const totalSteps = computed(() => selectedTemplate.value?.role_sequence.length ?? 0)
const currentRole = computed(() => selectedTemplate.value?.role_sequence[wizardStep.value] ?? null)
const selectedInRole = computed<Set<string>>(() => {
const role = currentRole.value?.display
if (!role) return new Set()
return new Set(roleOverrides.value[role] ?? [])
})
const priorPicks = computed<string[]>(() => {
if (!selectedTemplate.value) return []
return selectedTemplate.value.role_sequence
.slice(0, wizardStep.value)
.flatMap((r) => roleOverrides.value[r.display] ?? [])
})
const filteredCompatible = computed(() => applyFilter(candidates.value?.compatible ?? []))
const filteredOther = computed(() => applyFilter(candidates.value?.other ?? []))
function applyFilter(items: RoleCandidatesResponse['compatible']) {
if (recipesStore.builderFilterMode === 'text') {
const q = filterText.value.trim().toLowerCase()
if (!q) return items
return items.filter((i) => i.name.toLowerCase().includes(q))
} else {
if (selectedTags.value.size === 0) return items
return items.filter((i) =>
[...selectedTags.value].every((tag) => i.tags.includes(tag))
)
}
}
function toggleTag(tag: string) {
const next = new Set(selectedTags.value)
next.has(tag) ? next.delete(tag) : next.add(tag)
selectedTags.value = next
}
function toggleIngredient(name: string) {
const role = currentRole.value?.display
if (!role) return
const current = new Set(roleOverrides.value[role] ?? [])
current.has(name) ? current.delete(name) : current.add(name)
roleOverrides.value = { ...roleOverrides.value, [role]: [...current] }
}
function useCustomIngredient() {
const name = filterText.value.trim()
if (!name) return
const role = currentRole.value?.display
if (!role) return
// Add to role overrides so it's included in the build request
const current = new Set(roleOverrides.value[role] ?? [])
current.add(name)
roleOverrides.value = { ...roleOverrides.value, [role]: [...current] }
// Inject into the local candidates list so it renders as a selected card.
// Mark in_pantry: true so it stays visible regardless of missing-ingredient mode.
if (candidates.value) {
const knownNames = new Set([
...(candidates.value.compatible ?? []).map((i) => i.name.toLowerCase()),
...(candidates.value.other ?? []).map((i) => i.name.toLowerCase()),
])
if (!knownNames.has(name.toLowerCase())) {
candidates.value = {
...candidates.value,
compatible: [{ name, in_pantry: true, tags: [] }, ...(candidates.value.compatible ?? [])],
}
}
}
filterText.value = ''
}
async function selectTemplate(tmpl: AssemblyTemplateOut) {
selectedTemplate.value = tmpl
wizardStep.value = 0
roleOverrides.value = {}
phase.value = 'wizard'
await loadCandidates()
}
async function loadCandidates() {
if (!selectedTemplate.value || !currentRole.value) return
candidatesLoading.value = true
candidatesError.value = null
filterText.value = ''
selectedTags.value = new Set()
try {
candidates.value = await recipesAPI.getRoleCandidates(
selectedTemplate.value.id,
currentRole.value.display,
priorPicks.value,
)
} catch {
candidatesError.value = 'Could not load ingredient options. Please try again.'
} finally {
candidatesLoading.value = false
}
}
async function advanceStep() {
if (!selectedTemplate.value) return
if (wizardStep.value < totalSteps.value - 1) {
wizardStep.value++
await loadCandidates()
}
}
function goBack() {
if (phase.value === 'result') {
phase.value = 'wizard'
return
}
if (wizardStep.value > 0) {
wizardStep.value--
loadCandidates()
} else {
phase.value = 'select'
selectedTemplate.value = null
}
}
async function buildRecipe() {
if (!selectedTemplate.value) return
buildLoading.value = true
buildError.value = null
phase.value = 'result'
const overrides: Record<string, string> = {}
for (const [role, picks] of Object.entries(roleOverrides.value)) {
if (picks.length > 0) overrides[role] = picks[0]!
}
try {
builtRecipe.value = await recipesAPI.buildRecipe({
template_id: selectedTemplate.value.id,
role_overrides: overrides,
})
} catch {
buildError.value = 'Could not build recipe. Try adjusting your ingredients.'
} finally {
buildLoading.value = false
}
}
function resetToTemplate() {
phase.value = 'select'
selectedTemplate.value = null
wizardStep.value = 0
roleOverrides.value = {}
builtRecipe.value = null
buildError.value = null
}
onMounted(async () => {
templatesLoading.value = true
try {
templates.value = await recipesAPI.getTemplates()
} catch {
templatesError.value = 'Could not load templates. Please refresh.'
} finally {
templatesLoading.value = false
}
})
</script>
<style scoped>
.byo-tab {
padding: var(--spacing-sm) 0;
}
.byo-section {
max-width: 640px;
}
.template-grid {
display: grid;
grid-template-columns: repeat(2, 1fr);
gap: var(--spacing-sm);
}
@media (min-width: 640px) {
.template-grid {
grid-template-columns: repeat(3, 1fr);
}
}
.template-card {
display: flex;
flex-direction: column;
align-items: flex-start;
gap: var(--spacing-xs);
padding: var(--spacing-md);
text-align: left;
cursor: pointer;
}
.tmpl-icon {
font-size: 1.5rem;
}
.tmpl-title {
font-weight: 600;
font-size: 0.95rem;
}
.tmpl-descriptor {
line-height: 1.35;
}
.byo-nav {
display: flex;
align-items: center;
gap: var(--spacing-md);
}
.step-counter {
margin-left: auto;
}
.mode-toggle {
display: flex;
gap: var(--spacing-xs);
flex-wrap: wrap;
}
.filter-row {
display: flex;
gap: var(--spacing-xs);
align-items: flex-start;
}
.filter-input {
flex: 1;
}
.filter-mode-btn {
flex-shrink: 0;
min-width: 36px;
}
.tag-cloud {
flex: 1;
display: flex;
flex-wrap: wrap;
gap: var(--spacing-xs);
}
.tag-active {
background: var(--color-primary);
color: var(--color-bg-primary);
}
.ingredient-grid {
display: grid;
grid-template-columns: repeat(2, 1fr);
gap: var(--spacing-xs);
}
@media (min-width: 640px) {
.ingredient-grid {
grid-template-columns: repeat(3, 1fr);
}
}
.ingredient-card {
display: flex;
align-items: center;
justify-content: space-between;
padding: var(--spacing-sm) var(--spacing-md);
text-align: left;
min-height: 44px;
cursor: pointer;
}
.ingredient-active {
border: 2px solid var(--color-primary);
background: var(--color-primary-light);
color: var(--color-bg-primary);
}
.ingredient-missing {
opacity: 0.55;
}
.ingredient-name {
flex: 1;
font-size: 0.9rem;
}
.cart-icon {
font-size: 0.85rem;
margin-left: var(--spacing-xs);
}
.candidates-separator {
margin-top: var(--spacing-sm);
padding-top: var(--spacing-xs);
border-top: 1px solid var(--color-border);
}
.byo-actions {
display: flex;
gap: var(--spacing-sm);
flex-wrap: wrap;
}
.btn-link {
background: none;
border: none;
color: var(--color-primary);
cursor: pointer;
padding: 0;
text-decoration: underline;
}
.cart-list {
padding: var(--spacing-sm) var(--spacing-md);
}
.cart-items {
list-style: none;
display: flex;
flex-wrap: wrap;
gap: var(--spacing-xs);
margin-top: var(--spacing-xs);
}
.cart-item {
background: var(--color-bg-secondary);
border: 1px solid var(--color-border);
border-radius: var(--radius-sm);
padding: 2px var(--spacing-sm);
}
</style>

View file

@ -1,337 +1,231 @@
<!-- frontend/src/components/CommunityFeedPanel.vue -->
<template>
<div class="community-feed-panel">
<!-- Filter tabs: All / Plans / Successes / Bloopers -->
<div role="tablist" aria-label="Community post filters" class="filter-bar flex gap-xs mb-md">
<!-- Filter bar -->
<div class="filter-bar" role="toolbar" aria-label="Filter community posts">
<button
v-for="f in filters"
:key="f.id"
role="tab"
:aria-selected="activeFilter === f.id"
:tabindex="activeFilter === f.id ? 0 : -1"
:class="['btn', 'tab-btn', activeFilter === f.id ? 'btn-primary' : 'btn-secondary']"
@click="setFilter(f.id)"
@keydown="onFilterKeydown"
@pointerdown="f.id === 'recipe_blooper' ? onBlooperPointerDown($event) : undefined"
@pointerup="f.id === 'recipe_blooper' ? onBlooperPointerCancel() : undefined"
@pointerleave="f.id === 'recipe_blooper' ? onBlooperPointerCancel() : undefined"
v-for="f in FILTERS"
:key="f.value ?? 'all'"
class="filter-btn"
:class="{ active: activeFilter === f.value }"
:aria-pressed="activeFilter === f.value"
@click="setFilter(f.value)"
>{{ f.label }}</button>
</div>
<!-- Share a plan action row -->
<div class="action-row flex-between mb-sm">
<button
class="btn btn-secondary btn-sm share-plan-btn"
aria-haspopup="dialog"
@click="showPublishPlan = true"
>
Share a plan
<!-- Results count (aria-live so screen readers announce changes) -->
<p
class="results-summary"
aria-live="polite"
aria-atomic="true"
>
<template v-if="!loading">
{{ posts.length }} post{{ posts.length !== 1 ? 's' : '' }}
<template v-if="activeFilter"> · {{ activeFilterLabel }}</template>
</template>
</p>
<!-- Publish button (visible when plan is active) -->
<div class="publish-row" v-if="activePlanId">
<button class="publish-btn" @click="showPublish = true">
Share this week's plan
</button>
</div>
<!-- Loading skeletons -->
<div
v-if="store.loading"
class="skeleton-list flex-col gap-sm"
aria-busy="true"
aria-label="Loading posts"
>
<div v-for="n in 3" :key="n" class="skeleton-card">
<div class="skeleton-line skeleton-line-short"></div>
<div class="skeleton-line skeleton-line-long mt-xs"></div>
<div class="skeleton-line skeleton-line-med mt-xs"></div>
</div>
</div>
<!-- Error state -->
<div
v-else-if="store.error"
class="error-state card"
role="alert"
>
<p class="text-sm text-secondary mb-sm">{{ store.error }}</p>
<button class="btn btn-secondary btn-sm" @click="retry">
<div v-if="error" class="feed-error" role="alert">
<p>{{ error }}</p>
<button class="retry-btn" @click="communityStore.clearError(); communityStore.loadPosts(true)">
Try again
</button>
</div>
<!-- Empty state -->
<div
v-else-if="store.posts.length === 0"
class="empty-state card text-center"
>
<p class="text-secondary mb-xs">No posts yet</p>
<p class="text-sm text-muted">Be the first to share a meal plan or recipe story.</p>
</div>
<!-- Post list -->
<div v-else class="post-list flex-col gap-sm">
<!-- Feed -->
<div v-else-if="posts.length" class="feed-list">
<CommunityPostCard
v-for="post in store.posts"
v-for="post in posts"
:key="post.slug"
:post="post"
@fork="handleFork"
:forking="forkingSlug === post.slug"
@fork="onFork"
/>
<button
v-if="hasMore && !loading"
class="load-more-btn"
@click="communityStore.loadPosts()"
>
Load more
</button>
</div>
<!-- Loading skeleton -->
<div v-else-if="loading" class="feed-loading" aria-busy="true" aria-label="Loading posts">
<div v-for="i in 3" :key="i" class="skeleton-card"></div>
</div>
<!-- Empty state -->
<div v-else-if="isEmpty" class="feed-empty">
<p>No community posts yet.</p>
<p class="feed-empty-hint">Be the first to share a meal plan!</p>
</div>
<!-- Fork success toast -->
<Transition name="toast-fade">
<div
v-if="forkFeedback"
class="fork-toast status-badge status-success"
role="status"
aria-live="polite"
>
{{ forkFeedback }}
</div>
</Transition>
<div
v-if="forkSuccess"
class="fork-toast"
role="status"
aria-live="polite"
>
Plan forked into your week starting {{ forkSuccess.week_start }}
</div>
<!-- Fork error toast -->
<Transition name="toast-fade">
<div
v-if="forkError"
class="fork-toast status-badge status-error"
role="alert"
aria-live="assertive"
>
{{ forkError }}
</div>
</Transition>
<!-- Publish plan modal -->
<!-- Publish modal -->
<PublishPlanModal
v-if="showPublishPlan"
:plan="null"
@close="showPublishPlan = false"
@published="onPlanPublished"
v-if="showPublish"
:plan-id="activePlanId"
@close="showPublish = false"
@published="onPublished"
/>
<!-- Hall of Chaos easter egg: hold Bloopers tab for 800ms -->
<HallOfChaosView
v-if="showHallOfChaos"
@close="showHallOfChaos = false"
/>
</div>
</template>
<script setup lang="ts">
import { ref, onMounted, onUnmounted } from 'vue'
import { ref, computed, onMounted } from 'vue'
import { storeToRefs } from 'pinia'
import { useCommunityStore } from '../stores/community'
import type { ForkResult } from '../stores/community'
import CommunityPostCard from './CommunityPostCard.vue'
import PublishPlanModal from './PublishPlanModal.vue'
import HallOfChaosView from './HallOfChaosView.vue'
const emit = defineEmits<{
'plan-forked': [payload: ForkResult]
const props = defineProps<{
activePlanId?: number | null
}>()
const store = useCommunityStore()
const communityStore = useCommunityStore()
const { posts, loading, error, hasMore, isEmpty } = storeToRefs(communityStore)
const activeFilter = ref('all')
const showPublishPlan = ref(false)
const showHallOfChaos = ref(false)
let blooperHoldTimer: ReturnType<typeof setTimeout> | null = null
const activeFilter = ref<'plan' | 'recipe_success' | 'recipe_blooper' | null>(null)
const showPublish = ref(false)
const forkingSlug = ref<string | null>(null)
const forkSuccess = ref<{ plan_id: number; week_start: string } | null>(null)
function onBlooperPointerDown(_e: PointerEvent) {
blooperHoldTimer = setTimeout(() => {
showHallOfChaos.value = true
blooperHoldTimer = null
}, 800)
const FILTERS = [
{ label: 'All', value: null },
{ label: 'Plans', value: 'plan' as const },
{ label: 'Wins', value: 'recipe_success' as const },
{ label: 'Bloopers', value: 'recipe_blooper' as const },
] as const
const activeFilterLabel = computed(
() => FILTERS.find(f => f.value === activeFilter.value)?.label ?? ''
)
onMounted(() => communityStore.loadPosts(true))
function setFilter(value: typeof activeFilter.value) {
activeFilter.value = value
communityStore.setFilter(value)
}
function onBlooperPointerCancel() {
if (blooperHoldTimer !== null) {
clearTimeout(blooperHoldTimer)
blooperHoldTimer = null
async function onFork(slug: string) {
forkingSlug.value = slug
forkSuccess.value = null
const result = await communityStore.forkPost(slug)
forkingSlug.value = null
if (result) {
forkSuccess.value = result
setTimeout(() => { forkSuccess.value = null }, 4000)
}
}
const filters = [
{ id: 'all', label: 'All' },
{ id: 'plan', label: 'Plans' },
{ id: 'recipe_success', label: 'Successes' },
{ id: 'recipe_blooper', label: 'Bloopers' },
]
const filterIds = filters.map((f) => f.id)
function onFilterKeydown(e: KeyboardEvent) {
const current = filterIds.indexOf(activeFilter.value)
let next = current
if (e.key === 'ArrowRight') {
e.preventDefault()
next = (current + 1) % filterIds.length
} else if (e.key === 'ArrowLeft') {
e.preventDefault()
next = (current - 1 + filterIds.length) % filterIds.length
} else {
return
}
setFilter(filterIds[next]!)
// Move DOM focus to the newly active tab per ARIA tablist pattern
const bar = (e.currentTarget as HTMLElement).closest('[role="tablist"]')
const buttons = bar?.querySelectorAll<HTMLButtonElement>('[role="tab"]')
buttons?.[next]?.focus()
function onPublished() {
showPublish.value = false
communityStore.loadPosts(true)
}
async function setFilter(filterId: string) {
activeFilter.value = filterId
await store.fetchPosts(filterId === 'all' ? undefined : filterId)
}
async function retry() {
await store.fetchPosts(activeFilter.value === 'all' ? undefined : activeFilter.value)
}
const forkFeedback = ref<string | null>(null)
const forkError = ref<string | null>(null)
function showToast(msg: string, type: 'success' | 'error') {
if (type === 'success') {
forkFeedback.value = msg
setTimeout(() => { forkFeedback.value = null }, 3000)
} else {
forkError.value = msg
setTimeout(() => { forkError.value = null }, 4000)
}
}
async function handleFork(slug: string) {
try {
const result = await store.forkPost(slug)
showToast('Plan added to your week.', 'success')
emit('plan-forked', result)
} catch (err: unknown) {
showToast(err instanceof Error ? err.message : 'Could not fork this plan.', 'error')
}
}
function onPlanPublished(_payload: { slug: string }) {
showPublishPlan.value = false
store.fetchPosts(activeFilter.value === 'all' ? undefined : activeFilter.value)
}
onMounted(async () => {
if (store.posts.length === 0) {
await store.fetchPosts()
}
})
onUnmounted(() => {
if (blooperHoldTimer !== null) {
clearTimeout(blooperHoldTimer)
blooperHoldTimer = null
}
})
</script>
<style scoped>
.community-feed-panel {
position: relative;
}
.community-feed-panel { display: flex; flex-direction: column; gap: 0.75rem; }
.filter-bar {
border-bottom: 1px solid var(--color-border);
padding-bottom: var(--spacing-sm);
}
.tab-btn {
border-radius: var(--radius-md) var(--radius-md) 0 0;
border-bottom: none;
}
.action-row {
padding: var(--spacing-xs) 0;
}
.share-plan-btn {
font-size: var(--font-size-xs);
}
/* Loading skeletons */
.skeleton-card {
background: var(--color-bg-card);
.filter-bar { display: flex; gap: 6px; flex-wrap: wrap; }
.filter-btn {
font-size: 0.78rem;
padding: 0.25rem 0.75rem;
border-radius: 16px;
border: 1px solid var(--color-border);
border-radius: var(--radius-lg);
padding: var(--spacing-md);
overflow: hidden;
background: var(--color-surface);
color: var(--color-text-secondary);
cursor: pointer;
transition: background 0.15s, color 0.15s, border-color 0.15s;
}
.skeleton-line {
height: 12px;
border-radius: var(--radius-sm);
background: var(--color-bg-elevated);
animation: shimmer 1.4s ease-in-out infinite;
.filter-btn.active, .filter-btn:hover {
background: var(--color-accent-subtle);
color: var(--color-accent);
border-color: var(--color-accent);
}
.filter-btn:focus-visible { outline: 2px solid var(--color-accent); outline-offset: 2px; }
.skeleton-line-short { width: 35%; }
.skeleton-line-med { width: 60%; }
.skeleton-line-long { width: 90%; }
.results-summary { font-size: 0.75rem; color: var(--color-text-secondary); min-height: 1.1em; margin: 0; }
@keyframes shimmer {
0% { opacity: 0.6; }
50% { opacity: 1.0; }
100% { opacity: 0.6; }
.publish-row { display: flex; }
.publish-btn {
font-size: 0.82rem;
padding: 0.4rem 1.1rem;
border-radius: 20px;
background: var(--color-accent);
color: white;
border: none;
cursor: pointer;
transition: opacity 0.15s;
}
.publish-btn:hover { opacity: 0.88; }
.publish-btn:focus-visible { outline: 2px solid var(--color-accent); outline-offset: 2px; }
/* Empty / error states */
.empty-state {
padding: var(--spacing-xl) var(--spacing-lg);
.feed-list { display: flex; flex-direction: column; gap: 0.75rem; }
.load-more-btn {
align-self: center;
font-size: 0.8rem;
padding: 0.4rem 1.2rem;
border-radius: 16px;
border: 1px solid var(--color-border);
background: var(--color-surface);
color: var(--color-text-secondary);
cursor: pointer;
}
.load-more-btn:hover { border-color: var(--color-accent); color: var(--color-accent); }
.error-state {
padding: var(--spacing-md);
.feed-loading { display: flex; flex-direction: column; gap: 0.75rem; }
.skeleton-card {
height: 110px;
border-radius: 10px;
background: linear-gradient(90deg, var(--color-surface) 25%, var(--color-border) 50%, var(--color-surface) 75%);
background-size: 200% 100%;
animation: shimmer 1.4s infinite;
}
@media (prefers-reduced-motion: reduce) { .skeleton-card { animation: none; background: var(--color-surface); } }
@keyframes shimmer { 0% { background-position: 200% 0; } 100% { background-position: -200% 0; } }
/* Post list */
.post-list {
padding-top: var(--spacing-sm);
}
.feed-empty { text-align: center; padding: 2rem 0; color: var(--color-text-secondary); }
.feed-empty p { margin: 0.25rem 0; }
.feed-empty-hint { font-size: 0.82rem; opacity: 0.7; }
.feed-error { padding: 0.75rem 1rem; border-radius: 8px; background: color-mix(in srgb, red 8%, transparent); border: 1px solid color-mix(in srgb, red 20%, transparent); }
.feed-error p { margin: 0 0 0.5rem; font-size: 0.85rem; color: var(--color-text); }
.retry-btn { font-size: 0.78rem; padding: 0.3rem 0.8rem; border-radius: 14px; border: 1px solid currentColor; background: none; cursor: pointer; color: var(--color-accent); }
/* Toast */
.fork-toast {
position: fixed;
bottom: calc(72px + var(--spacing-md));
bottom: 1.5rem;
left: 50%;
transform: translateX(-50%);
z-index: 300;
white-space: nowrap;
box-shadow: var(--shadow-lg);
}
@media (min-width: 769px) {
.fork-toast {
bottom: var(--spacing-lg);
}
}
.toast-fade-enter-active,
.toast-fade-leave-active {
transition: opacity 0.3s ease, transform 0.3s ease;
}
.toast-fade-enter-from,
.toast-fade-leave-to {
opacity: 0;
transform: translateX(-50%) translateY(8px);
}
@media (prefers-reduced-motion: reduce) {
.skeleton-line {
animation: none;
opacity: 0.7;
}
.toast-fade-enter-active,
.toast-fade-leave-active {
transition: none;
}
.toast-fade-enter-from,
.toast-fade-leave-to {
transform: translateX(-50%);
}
background: var(--color-accent);
color: white;
padding: 0.6rem 1.2rem;
border-radius: 20px;
font-size: 0.85rem;
box-shadow: 0 4px 16px rgba(0,0,0,0.18);
z-index: 100;
pointer-events: none;
}
</style>

View file

@ -1,57 +1,56 @@
<!-- frontend/src/components/CommunityPostCard.vue -->
<template>
<article class="community-post-card" :class="`post-type-${post.post_type}`">
<!-- Header row: type badge + date -->
<div class="card-header flex-between gap-sm mb-xs">
<span
class="post-type-badge status-badge"
:class="typeBadgeClass"
:aria-label="`Post type: ${typeLabel}`"
>{{ typeLabel }}</span>
<time
class="post-date text-xs text-muted"
:datetime="post.published"
:title="fullDate"
>{{ shortDate }}</time>
</div>
<article class="post-card" :class="`post-type-${post.post_type}`">
<header class="post-header">
<span class="post-type-badge" :aria-label="`Post type: ${typeLabel}`">{{ typeLabel }}</span>
<time class="post-date" :datetime="post.published">{{ formattedDate }}</time>
</header>
<!-- Title -->
<h3 class="post-title text-base font-semibold mb-xs">{{ post.title }}</h3>
<h3 class="post-title">{{ post.title }}</h3>
<!-- Author -->
<p class="post-author text-xs text-muted mb-xs">
by {{ post.pseudonym }}
</p>
<p v-if="post.description" class="post-description">{{ post.description }}</p>
<!-- Description (if present) -->
<p v-if="post.description" class="post-description text-sm text-secondary mb-sm">
{{ post.description }}
</p>
<!-- Dietary tag pills -->
<div
v-if="post.dietary_tags.length > 0"
class="tag-row flex flex-wrap gap-xs mb-sm"
role="list"
aria-label="Dietary tags"
>
<div v-if="post.dietary_tags.length || post.allergen_flags.length" class="post-tags">
<span
v-for="tag in post.dietary_tags"
:key="tag"
class="status-badge status-success tag-pill"
role="listitem"
class="tag tag-dietary"
:aria-label="`Dietary: ${tag}`"
>{{ tag }}</span>
<span
v-for="flag in post.allergen_flags"
:key="flag"
class="tag tag-allergen"
:aria-label="`Contains: ${flag}`"
>{{ flag }}</span>
</div>
<!-- Fork button (plan posts only) -->
<div v-if="post.post_type === 'plan'" class="card-actions mt-sm">
<button
class="btn btn-primary btn-sm btn-fork"
:aria-label="`Fork ${post.title} to my meal plan`"
@click="$emit('fork', post.slug)"
>
Fork to my plan
</button>
<div v-if="post.post_type === 'plan' && post.slots.length" class="post-slots">
<span class="slots-summary">
{{ post.slots.length }} meal{{ post.slots.length !== 1 ? 's' : '' }} planned
</span>
</div>
<div v-if="post.outcome_notes" class="outcome-notes">
<p class="outcome-label">Notes</p>
<p class="outcome-text">{{ post.outcome_notes }}</p>
</div>
<footer class="post-footer">
<span class="post-author">by {{ post.pseudonym }}</span>
<div class="post-actions">
<button
v-if="post.post_type === 'plan'"
class="action-btn fork-btn"
:disabled="forking"
:aria-busy="forking"
@click="$emit('fork', post.slug)"
>
{{ forking ? 'Forking…' : 'Fork plan' }}
</button>
</div>
</footer>
</article>
</template>
@ -61,44 +60,24 @@ import type { CommunityPost } from '../stores/community'
const props = defineProps<{
post: CommunityPost
forking?: boolean
}>()
defineEmits<{
fork: [slug: string]
}>()
const typeLabel = computed(() => {
switch (props.post.post_type) {
case 'plan': return 'Meal Plan'
case 'recipe_success': return 'Success'
case 'recipe_blooper': return 'Blooper'
default: return props.post.post_type
}
})
const typeLabel = computed(() => ({
plan: 'Meal Plan',
recipe_success: 'Recipe Win',
recipe_blooper: 'Recipe Blooper',
}[props.post.post_type] ?? props.post.post_type))
const typeBadgeClass = computed(() => {
switch (props.post.post_type) {
case 'plan': return 'status-info'
case 'recipe_success': return 'status-success'
case 'recipe_blooper': return 'status-warning'
default: return 'status-info'
}
})
const shortDate = computed(() => {
const formattedDate = computed(() => {
try {
return new Date(props.post.published).toLocaleDateString('en-US', {
month: 'short',
day: 'numeric',
return new Date(props.post.published).toLocaleDateString(undefined, {
year: 'numeric', month: 'short', day: 'numeric',
})
} catch {
return ''
}
})
const fullDate = computed(() => {
try {
return new Date(props.post.published).toLocaleString()
} catch {
return props.post.published
}
@ -106,73 +85,87 @@ const fullDate = computed(() => {
</script>
<style scoped>
.community-post-card {
background: var(--color-bg-card);
.post-card {
background: var(--color-surface);
border: 1px solid var(--color-border);
border-radius: var(--radius-lg);
padding: var(--spacing-md);
transition: box-shadow 0.18s ease;
border-radius: 10px;
padding: 0.9rem 1rem;
display: flex;
flex-direction: column;
gap: 0.5rem;
transition: box-shadow 0.15s;
}
.post-card:hover { box-shadow: 0 2px 8px color-mix(in srgb, var(--color-accent) 12%, transparent); }
.community-post-card:hover {
box-shadow: var(--shadow-md);
}
.post-type-plan { border-left: 3px solid var(--color-info); }
.post-type-recipe_success { border-left: 3px solid var(--color-success); }
.post-type-recipe_blooper { border-left: 3px solid var(--color-warning); }
.card-header {
.post-header {
display: flex;
justify-content: space-between;
align-items: center;
gap: 0.5rem;
}
.post-type-badge {
font-size: 0.7rem;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 0.04em;
padding: 0.15rem 0.5rem;
border-radius: 20px;
background: var(--color-accent-subtle);
color: var(--color-accent);
}
.post-type-recipe_blooper .post-type-badge { background: color-mix(in srgb, orange 15%, transparent); color: #b36000; }
.post-type-recipe_success .post-type-badge { background: color-mix(in srgb, green 12%, transparent); color: #2a7a2a; }
.post-type-badge,
.post-date {
flex-shrink: 0;
}
.post-date { font-size: 0.75rem; color: var(--color-text-secondary); }
.post-title {
margin: 0;
color: var(--color-text-primary);
font-size: 0.95rem;
font-weight: 600;
color: var(--color-text);
line-height: 1.3;
}
.post-author,
.post-description {
margin: 0;
}
.post-description { margin: 0; font-size: 0.82rem; color: var(--color-text-secondary); line-height: 1.5; }
.post-description {
line-height: 1.5;
.post-tags { display: flex; flex-wrap: wrap; gap: 4px; }
.tag {
font-size: 0.68rem;
padding: 0.1rem 0.4rem;
border-radius: 10px;
border: 1px solid var(--color-border);
color: var(--color-text-secondary);
}
.tag-dietary { border-color: color-mix(in srgb, green 30%, transparent); color: #2a7a2a; }
.tag-allergen { border-color: color-mix(in srgb, orange 30%, transparent); color: #b36000; }
.tag-pill {
text-transform: lowercase;
}
.slots-summary { font-size: 0.78rem; color: var(--color-text-secondary); }
.card-actions {
.outcome-notes { background: var(--color-bg); border-radius: 6px; padding: 0.5rem 0.7rem; }
.outcome-label { margin: 0 0 0.2rem; font-size: 0.7rem; font-weight: 600; text-transform: uppercase; color: var(--color-text-secondary); }
.outcome-text { margin: 0; font-size: 0.82rem; color: var(--color-text); line-height: 1.5; }
.post-footer {
display: flex;
justify-content: flex-end;
justify-content: space-between;
align-items: center;
margin-top: 0.25rem;
flex-wrap: wrap;
gap: 0.4rem;
}
.post-author { font-size: 0.75rem; color: var(--color-text-secondary); font-style: italic; }
.btn-fork {
min-width: 120px;
}
@media (max-width: 480px) {
.community-post-card {
padding: var(--spacing-sm);
border-radius: var(--radius-md);
}
.btn-fork {
width: 100%;
}
}
@media (prefers-reduced-motion: reduce) {
.community-post-card {
transition: none;
}
.action-btn {
font-size: 0.78rem;
padding: 0.3rem 0.8rem;
border-radius: 16px;
border: 1px solid var(--color-accent);
background: var(--color-accent-subtle);
color: var(--color-accent);
cursor: pointer;
transition: background 0.15s;
}
.action-btn:hover:not(:disabled) { background: var(--color-accent); color: white; }
.action-btn:disabled { opacity: 0.5; cursor: default; }
.action-btn:focus-visible { outline: 2px solid var(--color-accent); outline-offset: 2px; }
</style>

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