docs(chat): record shared access and control behavior
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# Voyage Cursor Rules (local-only, gitignored)
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## Project Summary
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- Voyage is a self-hosted travel companion app (AdventureLog fork).
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- Stack: SvelteKit 2 + TypeScript frontend, Django REST Framework backend, PostgreSQL/PostGIS, Memcached, Docker, Bun.
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## Pre-Release Policy
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Voyage is **pre-release** — not yet in production use. During pre-release:
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- Architecture-level changes are allowed, including replacing core libraries (e.g. LiteLLM).
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- Prioritize correctness, simplicity, and maintainability over backward compatibility.
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- Before launch, this policy must be revisited and tightened for production stability.
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## Architecture Essentials
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- Frontend never calls Django directly.
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- Route all API requests through `frontend/src/routes/api/[...path]/+server.ts` (proxy to `http://server:8000`).
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- Services: `web:8015`, `server:8016`, `db:5432`, `cache` internal.
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- Auth: session-based (`django-allauth`), CSRF from `/auth/csrf/`, send `X-CSRFToken` for mutating requests.
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## Key Locations
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- Frontend: `frontend/src/`
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- Backend: `backend/server/`
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- Django apps: `adventures/`, `users/`, `worldtravel/`, `integrations/`, `achievements/`, `chat/`
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- Types: `frontend/src/lib/types.ts`
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- i18n: `frontend/src/locales/`
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## Commands
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- Frontend:
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- `cd frontend && bun run format`
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- `cd frontend && bun run lint`
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- `cd frontend && bun run check`
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- `cd frontend && bun run build`
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- `cd frontend && bun install`
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- Backend:
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- `docker compose exec server python3 manage.py test`
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- `docker compose exec server python3 manage.py migrate`
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- Use `uv` for local Python tooling when applicable
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- Docker:
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- `docker compose up -d`
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- `docker compose down`
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## Pre-Commit
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Run in order: format → lint → check → build.
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## Known Issues
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- `bun run check`: 0 errors + 6 warnings expected (pre-existing in `CollectionRecommendationView.svelte` + `RegionCard.svelte`).
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- Backend tests: 6/39 pre-existing failures expected (9 new chat tests all pass).
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- Docker dev setup may show frontend-backend 500 errors beyond homepage.
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## Conventions
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- Use `$t('key')` for user-facing strings.
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- Use DaisyUI semantic colors/classes (`bg-primary`, `text-base-content`).
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- Chat providers: dynamic catalog from `GET /api/chat/providers/`; configured in `CHAT_PROVIDER_CONFIG`.
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- Chat model override: dropdown selector fed by `GET /api/chat/providers/{provider}/models/`; per-provider persistence via `localStorage` key `voyage_chat_model_prefs`; backend `send_message` accepts optional `model`.
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- Chat context: collection chats inject collection UUID + multi-stop itinerary context; system prompt guides `get_trip_details`-first reasoning and confirms only before first `add_to_itinerary`.
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- Chat tool output: `role=tool` messages hidden from display; tool outputs render as concise summaries; persisted tool rows reconstructed on reload via `rebuildConversationMessages()`.
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- Chat errors: `_safe_error_payload()` maps LiteLLM exceptions to sanitized user-safe categories (never raw `exc.message`).
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- Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history.
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- Chat agent tools (`get_trip_details`, `add_to_itinerary`) respect collection sharing — both owners and `shared_with` members can use them; `list_trips` remains owner-only.
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- Do **not** attempt to fix known test/config issues during feature work.
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- Commit and merge completed feature branches promptly once validation passes (avoid leaving finished work unmerged).
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## .memory Files
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- At the start of any task, read `.memory/manifest.yaml` to discover available files, then read `system.md` and relevant `knowledge/` files for project context.
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- Read `.memory/decisions.md` for architectural decisions and review verdicts.
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- Check `.memory/plans/` and `.memory/research/` for prior work on related topics.
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- These files capture decisions, review verdicts, security findings, and plans from prior sessions.
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- Do **not** duplicate this info into code comments — `.memory/` is the source of truth for project history.
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## Instruction File Sync
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- `AGENTS.md`, `CLAUDE.md`, `.cursorrules`, and the Copilot CLI custom instructions must always be kept in sync.
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- Whenever any one is updated, apply the equivalent change to all the others.
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6
.github/copilot-instructions.md
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6
.github/copilot-instructions.md
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@@ -16,7 +16,7 @@ Voyage is **pre-release** — not yet in production use. During pre-release:
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**Key architectural pattern — API Proxy**: The frontend never calls the Django backend directly. All API calls go to `src/routes/api/[...path]/+server.ts`, which proxies requests to the Django server (`http://server:8000`), injecting CSRF tokens and managing session cookies. This means frontend fetches use relative URLs like `/api/locations/`.
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**AI Chat**: The AI travel chat assistant is embedded in Collections → Recommendations (component: `AITravelChat.svelte`). There is no standalone `/chat` route. Chat providers are loaded dynamically from `GET /api/chat/providers/` (backed by LiteLLM runtime list + custom entries like `opencode_zen`). Chat conversations stream via SSE through `/api/chat/conversations/`. Provider config lives in `backend/server/chat/llm_client.py` (`CHAT_PROVIDER_CONFIG`). Default AI provider/model saved via `UserAISettings` in DB (authoritative over browser localStorage). Chat composer supports per-provider model override via dropdown selector fed by `GET /api/chat/providers/{provider}/models/` (persisted in browser `localStorage` key `voyage_chat_model_prefs`). Collection chats inject collection UUID + multi-stop itinerary context; system prompt guides `get_trip_details`-first reasoning and confirms only before first `add_to_itinerary`. LiteLLM errors are mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history. Tool outputs render as concise summaries (not raw JSON); `role=tool` messages are hidden from display and reconstructed on reload via `rebuildConversationMessages()`.
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**AI Chat**: The AI travel chat assistant is embedded in Collections → Recommendations (component: `AITravelChat.svelte`). There is no standalone `/chat` route. Chat providers are loaded dynamically from `GET /api/chat/providers/` (backed by LiteLLM runtime list + custom entries like `opencode_zen`). Chat conversations stream via SSE through `/api/chat/conversations/`. Provider config lives in `backend/server/chat/llm_client.py` (`CHAT_PROVIDER_CONFIG`). Default AI provider/model saved via `UserAISettings` in DB (authoritative over browser localStorage). Chat composer supports per-provider model override via dropdown selector fed by `GET /api/chat/providers/{provider}/models/` (persisted in browser `localStorage` key `voyage_chat_model_prefs`). Collection chats inject collection UUID + multi-stop itinerary context; system prompt guides `get_trip_details`-first reasoning and confirms only before first `add_to_itinerary`. LiteLLM errors are mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history. Chat agent tools (`get_trip_details`, `add_to_itinerary`) respect collection sharing — both owners and `shared_with` members can use them; `list_trips` remains owner-only. Tool outputs render as concise summaries (not raw JSON); `role=tool` messages are hidden from display and reconstructed on reload via `rebuildConversationMessages()`.
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**Services** (docker-compose):
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- `web` → SvelteKit frontend at `:8015`
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@@ -75,7 +75,7 @@ Run these commands in order:
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**Backend (Django with Python — prefer uv for local tooling):**
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- Backend development requires Docker - local Python pip install fails due to network timeouts
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- `docker compose exec server python3 manage.py test` - **7 seconds** - Run tests (6/30 pre-existing failures expected)
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- `docker compose exec server python3 manage.py test` - **7 seconds** - Run tests (6/39 pre-existing failures expected; 9 chat tests all pass)
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- `docker compose exec server python3 manage.py help` - View Django commands
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- `docker compose exec server python3 manage.py migrate` - Run database migrations
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- Use `uv` for local Python dependency/tooling commands when applicable
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@@ -120,7 +120,7 @@ Run these commands in order:
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### Expected Test Failures
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- Frontend check: 0 errors and 6 warnings expected (pre-existing in `CollectionRecommendationView.svelte` + `RegionCard.svelte`)
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- Backend tests: 6 out of 30 Django tests fail (pre-existing: 2 user email key errors + 4 geocoding API mocks) - **DO NOT fix unrelated test failures**
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- Backend tests: 6 out of 39 Django tests fail (pre-existing: 2 user email key errors + 4 geocoding API mocks; 9 new chat tests all pass) - **DO NOT fix unrelated test failures**
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### Build Timing (NEVER CANCEL)
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- **Docker first startup**: 25+ minutes (image downloads)
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@@ -9,6 +9,7 @@
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## Backend Patterns
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- **Views**: DRF `ModelViewSet` subclasses; `get_queryset()` filters by `user=self.request.user`
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- **Shared-access queries**: Use `Q(user=user) | Q(shared_with=user)).distinct()` for collection lookups that should include shared members (e.g. chat agent tools). Always `.distinct()` to avoid `MultipleObjectsReturned` when owner is also in `shared_with`.
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- **Money**: `djmoney` MoneyField
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- **Geo**: PostGIS via `django-geojson`
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- **Chat providers**: Dynamic catalog from `GET /api/chat/providers/`; configured in `CHAT_PROVIDER_CONFIG`
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@@ -26,6 +26,12 @@
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- On unshare/leave, departing user's locations are removed from collection (not deleted)
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- `duplicate` action creates a private copy with no `shared_with` transfer
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### Chat Agent Tool Access
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- `get_trip_details` and `add_to_itinerary` tools authorize using `Q(user=user) | Q(shared_with=user)` — shared members can use AI chat tools on shared collections.
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- `list_trips` remains owner-only (shared collections not listed).
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- `add_to_itinerary` assigns `Location.user = shared_user` (shared users own their contributed locations), consistent with REST API behavior.
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- See [patterns/chat-and-llm.md](../patterns/chat-and-llm.md#shared-trip-tool-access).
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## Itinerary Architecture
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### Primary Component
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@@ -10,10 +10,11 @@ Frontend never calls Django directly. All API calls go through `src/routes/api/[
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- Chat conversations stream via SSE through `/api/chat/conversations/`.
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- `ChatViewSet.send_message()` accepts optional context fields (`collection_id`, `collection_name`, `start_date`, `end_date`, `destination`) and appends a `## Trip Context` section to the system prompt when provided. When a `collection_id` is present, also injects `Itinerary stops:` from `collection.locations` (up to 8 unique stops) and the collection UUID with explicit `get_trip_details`/`add_to_itinerary` grounding. See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#trip-context-uuid-grounding) and [patterns/chat-and-llm.md](patterns/chat-and-llm.md#multi-stop-context-derivation).
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- Chat composer supports per-provider model override (persisted in browser `localStorage` key `voyage_chat_model_prefs`). DB-saved default provider/model (`UserAISettings`) is authoritative on initialization; localStorage is write-only sync target. Backend `send_message` accepts optional `model` param; falls back to DB defaults → instance defaults → `"openai"`.
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- Chat agent tools (`get_trip_details`, `add_to_itinerary`) authorize using `Q(user=user) | Q(shared_with=user)` — both owners and shared members can use them. `list_trips` remains owner-only. See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#shared-trip-tool-access).
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- Invalid required-argument tool calls are detected and short-circuited: stream terminates with `tool_validation_error` SSE event + `[DONE]` and invalid tool results are not replayed into conversation history. See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#tool-call-error-handling-chat-loop-hardening).
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- LiteLLM errors mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#sanitized-llm-error-mapping).
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- Tool outputs display as concise summaries (not raw JSON) via `getToolSummary()`. Persisted `role=tool` messages are hidden from display; on conversation reload, `rebuildConversationMessages()` reconstructs `tool_results` on assistant messages. See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#tool-output-rendering).
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- Embedded chat uses compact header (provider/model selectors in settings dropdown), bounded height, sidebar-closed-by-default, and visible streaming indicator. See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#embedded-chat-ux).
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- Embedded chat uses compact header (provider/model selectors in settings dropdown with outside-click/Escape close), bounded height, sidebar-closed-by-default, visible streaming indicator, and i18n aria-labels. See [patterns/chat-and-llm.md](patterns/chat-and-llm.md#embedded-chat-ux).
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- Frontend type: `ChatProviderCatalogEntry` in `src/lib/types.ts`.
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- Reference: [Plan: AI travel agent](../plans/ai-travel-agent-collections-integration.md), [Plan: AI travel agent redesign — WS4](../plans/ai-travel-agent-redesign.md#ws4-collection-level-chat-improvements)
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@@ -41,7 +41,12 @@
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- UUID injection only occurs when collection lookup succeeds AND user is owner or `shared_with` member (authorization gate).
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- System prompt includes two-phase confirmation guidance: confirm only before the **first** `add_to_itinerary` action; after explicit user approval phrases ("yes", "go ahead", "add them"), proceed directly without re-confirming.
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- `get_trip_details` DoesNotExist returns `"collection_id is required and must reference a trip you can access"` (does NOT match short-circuit regex due to `fullmatch` — correct, this is an invalid-value error, not missing-param).
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- Known pre-existing: `get_trip_details` filters `user=user` only — shared-collection members get UUID context but tool returns DoesNotExist. Low severity.
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### Shared-Trip Tool Access
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- `get_trip_details` and `add_to_itinerary` authorize collections using `Q(user=user) | Q(shared_with=user)` with `.distinct()` — both owners and shared members can access.
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- `list_trips` remains owner-only by design.
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- `.distinct()` prevents `MultipleObjectsReturned` when the owner is also present in `shared_with`.
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- Non-members receive `DoesNotExist` errors through existing error paths.
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## Tool Output Rendering
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- Frontend `AITravelChat.svelte` hides raw `role=tool` messages via `visibleMessages` filter (`messages.filter(msg => msg.role !== 'tool')`).
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@@ -62,7 +67,8 @@
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- Sidebar defaults to closed in embedded mode (`let sidebarOpen = !embedded;`); `lg:flex` ensures always-visible on desktop.
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- Quick-action chips use `btn-xs` + `overflow-x-auto` for compact embedded fit.
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- Streaming indicator visible inside last assistant bubble throughout entire generation (conditioned on `isStreaming && msg.id === lastVisibleMessageId`).
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- Known low-priority: `aria-label` values on sidebar toggle and settings button are hardcoded English (should use `$t()`). `<details>` dropdown does not auto-close on outside click.
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- Aria-label values on sidebar toggle and settings button use i18n keys (`chat_a11y.show_conversations_aria`, `chat_a11y.hide_conversations_aria`, `chat_a11y.ai_settings_aria`); key parity across all 20 locale files.
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- Settings dropdown closes on outside click (`pointerdown`/`mousedown`/`touchstart` listeners) and `Escape` keypress, with mount-time listener cleanup.
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## OpenCode Zen Provider
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- Provider ID: `opencode_zen`
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@@ -13,7 +13,7 @@ Voyage is **pre-release** — not yet in production use. During pre-release:
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## Architecture Overview
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- **API proxy pattern**: Frontend never calls Django directly. All API calls go through `frontend/src/routes/api/[...path]/+server.ts`, which proxies to `http://server:8000`, handles cookies, and injects CSRF behavior.
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- **AI chat**: Embedded in Collections → Recommendations via `AITravelChat.svelte` component. No standalone `/chat` route. Provider list is dynamic from backend `GET /api/chat/providers/` (sourced from LiteLLM runtime + custom entries like `opencode_zen`). Chat conversations use SSE streaming via `/api/chat/conversations/`. Default AI provider/model saved via `UserAISettings` in DB (authoritative over browser localStorage). LiteLLM errors are mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history.
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- **AI chat**: Embedded in Collections → Recommendations via `AITravelChat.svelte` component. No standalone `/chat` route. Provider list is dynamic from backend `GET /api/chat/providers/` (sourced from LiteLLM runtime + custom entries like `opencode_zen`). Chat conversations use SSE streaming via `/api/chat/conversations/`. Default AI provider/model saved via `UserAISettings` in DB (authoritative over browser localStorage). LiteLLM errors are mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history. Chat agent tools (`get_trip_details`, `add_to_itinerary`) respect collection sharing — both owners and `shared_with` members can use them; `list_trips` remains owner-only.
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- **Service ports**:
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- `web` → `:8015`
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- `server` → `:8016`
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@@ -57,7 +57,7 @@ Run in this order:
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## Known Issues (Expected)
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- Frontend `bun run check`: **0 errors + 6 warnings** expected (pre-existing in `CollectionRecommendationView.svelte` + `RegionCard.svelte`)
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- Backend tests: **6/30 fail** (pre-existing: 2 user email key errors + 4 geocoding API mocks)
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- Backend tests: **6/39 fail** (pre-existing: 2 user email key errors + 4 geocoding API mocks; 9 new chat tests all pass)
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- Docker dev setup has frontend-backend communication issues (500 errors beyond homepage)
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## Key Patterns
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@@ -15,7 +15,7 @@ Voyage is **pre-release** — not yet in production use. During pre-release:
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- Use the API proxy pattern: never call Django directly from frontend components.
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- Route all frontend API calls through `frontend/src/routes/api/[...path]/+server.ts`.
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- Proxy target is `http://server:8000`; preserve session cookies and CSRF behavior.
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- AI chat is embedded in Collections → Recommendations via `AITravelChat.svelte`. There is no standalone `/chat` route. Chat providers are loaded dynamically from `GET /api/chat/providers/` (backed by LiteLLM runtime providers + custom entries like `opencode_zen`). Chat conversations stream via SSE through `/api/chat/conversations/`. Default AI provider/model saved via `UserAISettings` in DB (authoritative over browser localStorage). LiteLLM errors are mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history.
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- AI chat is embedded in Collections → Recommendations via `AITravelChat.svelte`. There is no standalone `/chat` route. Chat providers are loaded dynamically from `GET /api/chat/providers/` (backed by LiteLLM runtime providers + custom entries like `opencode_zen`). Chat conversations stream via SSE through `/api/chat/conversations/`. Default AI provider/model saved via `UserAISettings` in DB (authoritative over browser localStorage). LiteLLM errors are mapped to sanitized user-safe messages via `_safe_error_payload()` (never exposes raw exception text). Invalid tool calls (missing required args) are detected and short-circuited with a user-visible error — not replayed into history. Chat agent tools (`get_trip_details`, `add_to_itinerary`) respect collection sharing — both owners and `shared_with` members can use them; `list_trips` remains owner-only.
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- Service ports:
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- `web` → `:8015`
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- `server` → `:8016`
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@@ -65,7 +65,7 @@ Run in this exact order:
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## Known Issues (Expected)
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- Frontend `bun run check`: **0 errors + 6 warnings** expected (pre-existing in `CollectionRecommendationView.svelte` + `RegionCard.svelte`)
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- Backend tests: **6/30 fail** (pre-existing: 2 user email key errors + 4 geocoding API mocks)
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- Backend tests: **6/39 fail** (pre-existing: 2 user email key errors + 4 geocoding API mocks; 9 new chat tests all pass)
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- Docker dev setup has frontend-backend communication issues (500 errors beyond homepage)
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## Key Patterns
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Reference in New Issue
Block a user