Fix final review findings: key leak, model fallback, error resilience, docs

- ApiClient: strip query string from ApiError messages so API keys
  (e.g. TMDb's api_key query param) never leak into 500 response
  bodies or logs.
- LlmTool: accept an optional defaultModel, wired from AppConfig's
  LLM_MODEL, so Langfuse prompts that omit a model config fall back
  to the configured LLM rather than silently requesting gpt-4o-mini.
- RecommendationPipeline: restore the Go original's graceful
  degradation — library/Radarr fetch failures, per-suggestion TMDb
  resolution failures, and per-signal TMDb similarity/recommendation
  failures are now logged and skipped instead of aborting the whole
  run (applies to both runInternal and searchAsync).
- RecommendationsController: validate the ?count= query param
  (must be a positive integer) instead of silently producing NaN.
- Commit the Langfuse prompt definitions (langfuse/*.prompt.json) and
  add a README covering setup, prompt seeding, cache invalidation,
  and the HTTP API surface — the branch was not otherwise runnable by
  anyone but the author.

README.md

@@ -0,0 +1,94 @@
+# sugarr
+
+Movie-recommendation companion for Jellyfin: pulls your favorite/recently-watched
+movies, gets suggestions from an LLM (via Langfuse-managed prompts) or a TMDb
+similarity/frequency fallback, resolves them against TMDb, excludes anything
+already in your library or Radarr, and can auto-request the rest via Radarr.
+Runs on a cron schedule and/or as an HTTP API.
+
+This repo currently has two implementations:
+
+- **`cmd/`, `internal/`** — the original Go implementation.
+- **`src/`** — a TypeScript/OOP rewrite (Node + Fastify + Langfuse), the one
+  documented below. See `docs/superpowers/specs/2026-08-12-typescript-oop-rewrite-design.md`
+  and `docs/superpowers/plans/2026-08-12-typescript-oop-rewrite.md` for the
+  design and implementation plan.
+
+## Running the TypeScript app
+
+```bash
+pnpm install
+cp .env.example .env   # fill in the values below
+pnpm dev                # or: pnpm build && pnpm start
+```
+
+### Required environment variables
+
+See `.env.example` for the full list with defaults. At minimum you need:
+
+- `JELLYFIN_URL`, `JELLYFIN_API_KEY`, `JELLYFIN_USER_ID`, `TMDB_API_KEY`
+- `LANGFUSE_PUBLIC_KEY`, `LANGFUSE_SECRET_KEY`, `LANGFUSE_BASE_URL` — the app
+  fetches its LLM prompts from Langfuse at runtime (see below), so these are
+  required even if `LLM_ENABLED=false` (only the recommend/search endpoints
+  actually call Langfuse; if you never enable the LLM path you can point
+  these at any reachable Langfuse instance).
+
+### Docker
+
+```bash
+docker compose -f docker-compose.node.yml up -d --build
+```
+
+Uses `Dockerfile.node` / `docker-compose.node.yml`, kept separate from the Go
+app's `Dockerfile` / `docker-compose.yml`.
+
+## Seeding Langfuse prompts
+
+The app fetches two chat prompts from Langfuse by name — `movie-recommender`
+and `movie-search` — compiles them with per-request variables, and reads
+model/temperature/etc. from each prompt version's `config` field. Ready-to-import
+definitions are in `langfuse/`:
+
+- `langfuse/movie-recommender.prompt.json`
+- `langfuse/movie-search.prompt.json`
+
+Create each one in your Langfuse project (UI: **Prompts → New prompt**, type
+**Chat**; or via the Langfuse API/SDK) using the `prompt` array as the chat
+messages and the `config` object as the prompt's config. Variables use
+`{{name}}` interpolation:
+
+- `movie-recommender`: `count`, `favorites`, `watched`, `library`, `previouslySuggested`
+- `movie-search`: `query`, `count`
+
+## Prompt caching and invalidation
+
+Compiled prompts are cached in memory per process (`LANGFUSE_PROMPT_CACHE_ENABLED`,
+default `true`; set to `false` to always fetch fresh from Langfuse — useful
+while iterating on a prompt). To invalidate the cache after updating a prompt
+in Langfuse without restarting the app, call:
+
+```
+POST /webhooks/langfuse/invalidate
+Content-Type: application/json
+Authorization: Bearer <SECRET_KEY>   # if SECRET_KEY is set
+
+{"promptName": "movie-recommender"}   # or {} / omit body to clear the whole cache
+```
+
+This isn't wired to a Langfuse-native push webhook (self-hosted Langfuse has
+no built-in "prompt updated" event) — call it manually, from CI after a prompt
+change, or from Langfuse Cloud's webhook feature if you have one configured.
+
+## HTTP API
+
+| Method | Path | Notes |
+|---|---|---|
+| GET | `/health` | exempt from auth |
+| GET | `/recommendations` | `?count=`, `?force_llm=true`, `?force_tmdb=true` |
+| POST | `/recommendations/search` | body `{"query": "..."}`, requires `LLM_ENABLED=true` |
+| POST | `/recommendations/trigger` | runs the pipeline + auto-requests via Radarr if enabled |
+| POST | `/recommendations/request` | body `{"tmdb_id": 12345}`, requires `RADARR_ENABLED=true` |
+| POST | `/webhooks/langfuse/invalidate` | body `{"promptName"?: string}` |
+
+If `SECRET_KEY` is set, all routes except `/health` require
+`Authorization: Bearer <SECRET_KEY>`.