# Architecture (backend) Single Bun process: `Bun.serve` handles the JSON/SSE API **and** the static frontend (same origin, no CORS). Persistence is SQLite via Bun's native `bun:sqlite` driver (`$DATA_DIR/kisassistant.db`, WAL mode). ``` browser ──► Bun.serve (src/index.ts) ├─ /api/* ──► auth gate ──► routes ──► db.ts ──► kisassistant.db │ └─────► DriverRegistry ──► ollama / APIs └─ /* ──► static files + SPA fallback (index.html, covers /share/:id) ``` ## Request flow: chat `POST /api/chat { model: "driver:model", messages, conversationId?, stream? }` 1. Bearer token → `verifyToken` (sha256 lookup in `sessions`, expiry check). 2. `DriverRegistry.splitId` routes to the owning driver (unknown/disabled → 400). 3. If `conversationId` is set: conversation must belong to the caller, the new user message is stored (deduped against the last stored message), new chats are auto-titled from it. 4. Non-streaming → `driver.chat()` → JSON. Streaming → `driver.chatStream()` → SSE events `token` / `done` / `error`. The full reply is persisted after a successful stream; on error the partial text is kept as-is (no internal markers). Server logs each stream open/done/abort per driver when `DRIVER_DEBUG=true`. Streaming guarantees (ChatGPT-style, no buffering): - Tokens are forwarded via `controller.enqueue` the moment they arrive from the LLM; disconnects are detected (`req.signal`, guarded `enqueue`, stream `cancel()`) and propagated upstream via an `AbortController` passed as `opts.signal`, so the model stops generating when the tab closes. - `Bun.serve` runs with `idleTimeout: 0` — the default 10 s would kill slow streams (cold model load, thinking pauses) mid-generation. - Responses carry `X-Accel-Buffering: no` and the NixOS nginx vhost sets `proxy_buffering off`, otherwise the proxy would buffer the whole reply. ## Database schema Created idempotently at boot in `getDb()` (no migration framework; keep it so). | Table | Purpose | |---|---| | `users` | `id, username UNIQUE, display_name, avatar_url, theme, key_hash, created_at`. The `admin` row is bootstrapped (its `key_hash` is unused — admin auth goes through `APP_PASSWORD`). | | `sessions` | `token_hash PK, user_id, created_at, expires_at`. Bearer tokens, 256-bit, hashed with sha256. Expired rows are purged lazily on access. | | `conversations` | `id, user_id, title, topic, model, created_at, updated_at`. | | `messages` | `id AUTOINCREMENT, conv_id → conversations ON DELETE CASCADE, role, content, created_at`. | | `shares` | `conv_id PK → conversations ON DELETE CASCADE, public_id UNIQUE, created_at`. | User deletion cascades manually in `deleteUser()` (messages → shares → conversations → sessions → user) inside a transaction. ## Auth - `POST /api/auth/login { username, key }`, sliding-window rate limit per IP (`RATE_LIMIT_MAX` / `RATE_LIMIT_WINDOW_MIN`, default 5 per 10 min) + 400 ms delay on failure. Success clears the IP counter and issues a fresh token. - `admin` is authenticated against `APP_PASSWORD` (timing-safe); users against their `ka_…` access key (timing-safe against the stored hash). - Keys are generated with `crypto.randomBytes` (`ka_` + 24 bytes base64url) and **returned once** at creation/regeneration. Regeneration also wipes the account's sessions. ## Drivers `src/drivers/`: `LLMDriver` interface (`listModels`, `chat`, `chatStream`), `DriverRegistry` with global priority `ollama → mistral → puppeteer-openai (stub) → deepseek → anthropic → openai`. Models are addressed as `"driver:model"` (split on the first `:`). - `OllamaDriver`: model discovery via `GET {OLLAMA_HOST}/api/tags`, chat via `POST /api/chat` with NDJSON streaming. - `ApiDriverBase`: shared OpenAI-compatible `/models` + `/chat/completions` (SSE) implementation; concrete drivers only set base URL, key, and fallback model list. A driver is enabled only when its `*_ENABLED` flag is set **and** its key is non-empty; failing drivers are skipped (not fatal) in listings. - `PuppeteerOpenAIDriver`: intentional stub, always disabled (headless scraping of chatgpt.com is fragile and against ToS).