F9-lite reuses the pre-existing OLLAMA_* config (config.py:36-38:
OLLAMA_BASE_URL=https://ollama.com/v1, OLLAMA_API_KEY,
OLLAMA_MODEL=kimi-k2.6:cloud). Avoids the local model pull
(F9-full would be 4 GB on disk + a separate uvicorn process).
Cloud LLM — operator’s existing OLLAMA billing applies per call.
Sprint 13 splits the Sprint 11 "Generate Meal Plan" CTA into a
2-step modal: "Use the recipe library" (default, Sprint 11’s
existing flow) or "Ask the LLM" (new). The LLM path POSTs to
/api/llm/plan with a free-text prompt; the backend calls
kimi-k2.6:cloud on ollama.com, parses the LLM’s JSON picks,
creates a fresh plan, fills the LLM’s picks, and falls through
to the Sprint 6+ fillEmptySlots pattern for the slots the LLM
didn’t cover.
Backend:
- backend/app/api/llm_plan.py (NEW, ~280 lines). 1 endpoint
(POST /api/llm/plan body {prompt, week_start}) + 4 helpers:
- _ensure_ollama_configured — 503 on missing OLLAMA_API_KEY.
- _serialize_library — reads up to 200 recipes for the
family, sorted alphabetically. Cap prevents prompt-token
overflow on kimi-k2.
- _ask_llm — mirrors llm_matcher._ask_ollama (same URL,
same headers, max_tokens=800, temperature=0, strips think
blocks, 60s timeout).
- _parse_picks — tolerant JSON parser. Handles markdown code
fences, trailing commentary, and bare JSON. On failure
returns []; the library fill takes over.
- _validate_picks — drops invalid entries: missing fields,
out-of-range day_of_week, unknown meal_type, unknown
recipe_id. Returns a list of LLMPickedItem.
Flow: rejects duplicate week (400) and empty library (400),
builds the prompt, calls the LLM, validates picks, creates
the plan, inserts the LLM-picked items, fills the rest from
the library (Sprint 6+ pattern, re-implemented inline to
avoid a self-HTTP-call), returns {plan_id, picked_count,
filled_count, failed_count, reasoning}.
- backend/app/schemas/__init__.py — added LLMPlanRequest +
LLMPlanResponse.
- backend/app/main.py:65-66 — registered llm_plan_api.router
at the /api/llm prefix. No collision with the pre-existing
WIP recipes.py.
Frontend:
- frontend/src/api/index.ts — added llm.plan(data) method.
- frontend/src/pages/Dashboard.tsx — added the prompt modal
(radio for library vs. LLM + textarea for the LLM path with
500-char counter) + new state (showPromptModal, promptMode,
promptText, promptBusy) + extracted Sprint 11’s body into
generateFromLibrary + added generateFromLLM. The modal is
inline (not a separate component) because it depends on 4
local states + 3 handlers. Click-outside-to-dismiss is
disabled while promptBusy is true. The textarea autoFocuses
when LLM mode is selected. Added the Button import.
LLM tolerance: a 60s timeout, parse-failure (markdown code
fences, trailing commentary), or empty response all return 0
picks; the library fill takes over. The user never sees a
crash — at worst, picked_count: 0 and the toast reads "Planned
N meals (LLM picked 0, library filled the rest)".
Verified: npm run build green (tsc 0 errors, vite 0 errors).
Bundle: 500.28 → 503.82 kB (+3.5 kB). Backend AST clean on
all 3 changed files. No new dependencies, no migration, no
pre-existing WIP files touched.
Deploy: git pull + docker compose up -d --build backend
frontend (no migration, no new dependencies).
Sprint 12 wires a "Search the web" toggle on /recipes that hits
Spoonacular’s complexSearch API. Each result has an "Import"
button that pulls the full recipe info (1 point) and writes a
local Recipe row with the right schema fields. Spoonacular
ingredients are upserted into the local Ingredient table via the
existing idempotent logic (mirrors POST /api/ingredients without
the HTTP roundtrip).
No pre-existing WIP files touched. Sprint 12 creates a new
backend/app/api/recipe_search.py router (separate from the WIP
recipes.py) and adds 2 Pydantic models to backend/app/schemas/
__init__.py (the canonical location). The WIP recipes.py is
registered in main.py (lines 54-55) and handles GET /api/recipes,
GET /api/recipes/recommended, GET /api/recipes/{id} — none of
which collide with my new endpoints.
Backend:
- backend/app/api/recipe_search.py (NEW, ~270 lines). 2 endpoints:
- GET /api/recipes/search?q=&limit= — calls complexSearch with
addRecipeInformation=true, fillIngredients=true,
instructionsRequired=true. Returns normalized
RecipeSearchHit[]. NO info endpoint call (saves 1 pt per
result; the pre-existing _search_spoonacular calls the info
endpoint for every result, burning the whole daily quota on a
10-result search).
- POST /api/recipes/import — fetches /recipes/{id}/information
(1 pt), normalizes, upserts ingredients via the existing
idempotent helper, creates a local Recipe with
external_source="spoonacular" + external_id +
is_manually_added=True, returns the new recipe id.
- Process-wide _points_used counter (module-level singleton +
threading.Lock). 503 with detail: "spoonacular daily quota
reached; try again tomorrow" when over 140 (10-pt safety
margin under the 150-pt free tier). Resets on process restart.
- 503 with clear "SPOONACULAR_API_KEY not configured" when env
var unset.
- Idempotent import: 409 on duplicate (external_source,
external_id).
- backend/app/config.py — added SPOONACULAR_API_KEY: Optional[str]
to Settings (was previously read via getattr since extra=ignore).
- backend/app/schemas/__init__.py — added RecipeSearchHit +
RecipeImportRequest.
- backend/app/main.py:62-63 — registered recipe_search_api.router
at the /api/recipes prefix. No collision with the WIP.
Frontend:
- frontend/src/api/index.ts — added 5 new methods to
mealPlannerApi.recipes: search, importRecipe, recommended,
listIngredients, createIngredient. The last 3 are stubs for
pre-existing call sites in Pantry/MealDetail/Recommended.tsx
that were previously hidden by a smaller API surface.
- frontend/src/pages/Recipes.tsx — added searchWeb toggle state
+ importedExternalIds set + webHits query (enabled: searchWeb &&
debouncedQ.length >= 2) + importMutation (toast on success,
showApiError on failure) + the toggle button (with
aria-pressed={searchWeb}) + the web-search panel (<div
role="region" aria-label="Web recipe search"
aria-busy={webLoading}>). The panel reuses the existing q +
handleSearch (300ms debounce) so the local search bar drives
both. The Import button has a 3-state machine: Import
(Sparkles) → Importing… (Loader2) → Imported (Check, disabled).
- frontend/src/types/index.ts — added optional ingredient +
is_optional to RecipeIngredient (for pre-existing MealDetail.tsx
call sites).
Verified: npm run build green (tsc 0 errors, vite 0 errors).
Bundle: 496.48 → 500.28 kB (+3.8 kB). Backend AST clean on all 4
changed files. Backend pytest skipped (venv on docker-willester
is broken, pre-existing).
Deploy: git pull + docker compose up -d --build backend frontend
(backend has the new router; frontend has the new toggle). No
migration, no new dependencies.
- api/meal_plans.py: /regenerate now passes exclude_recipe_ids into generate_meal_plan
- planner/generate.py: filter recipe_dicts by exclude_recipe_ids set
- image_generation.py: OpenAI gpt-image-1 client with prompt building, b64_json handling
- main.py: StaticFiles mount at /static for generated images
- admin.py: POST /api/admin/trigger-images endpoint for batch generation
- scripts/generate_images.py: CLI for batch image generation
- docker-compose.yml + nginx: volume mounts for static/images persistence
- Verify MealPlanItem.votes ↔ MealPlanVote relationship is correct; no model bug exists
- Create backend/app/api/orchestrate.py — new router for workflow steps
(scrape, generate, email, reminder, deadline, finalize) without admin auth.
- Remove orchestrate endpoints from backend/app/api/admin.py.
- Register orchestrate router in main.py under /api/orchestrate.
- Update frontend api/index.ts to call /orchestrate/{step} instead of
/admin/orchestrate/{step}.
This lets family members trigger vote emails without an admin bearer token.
POST/PATCH validate every ingredient_id against the ingredient table
and return 422 with the missing list when refs don't resolve. Replaces
the prior recipes.py stub. Public read routes + admin write routes.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Backend (FastAPI):
- docker-compose with all 4 services
- FastAPI app with health endpoints
- SQLAlchemy models for all tables
- Placeholder API endpoints for all routes
- Config and database modules
- requirements.txt with all dependencies
Frontend (React):
- package.json with React, Tailwind, React Query, React Router
- Vite config with API proxy
- Tailwind and TypeScript configs
- Basic App with routing skeleton
- Placeholder pages (Dashboard, MealDetail, Pantry)
Infrastructure:
- nginx config for reverse proxy
- Dockerfile for backend and frontend
admin
