# Architecture > How the system is built and why. Update this when the structure changes; a change is > not finished until this reflects it. ## Overview Four parts, connected by an open REST API and a shared recording data model: ``` [ Device: ESP32-S3 ] [ Self-hosted server ] mic -> I2S -> ring buffer (PSRAM) FastAPI -> encoder (WAV) -> microSD +-- ingest (from cloud store / upload) button/LED/haptic UX +-- faster-whisper (transcribe) power + charge detect +-- Ollama LLM (summarise) | BLE (control/provision) +-- object store (MinIO/local) + DB | WiFi REST API (LAN) `-- open REST API + exports | WiFi uploader (on charge) --> cloud store -----------^ | | v v [ Flutter app: Android + iOS ] <---- open REST API (device + server) ``` Three sync paths, exactly as specified: 1. BLE: control, status, and WiFi provisioning (small data). Portable/battery mode. 2. WiFi to app: bulk recording transfer via the device REST API (fast). 3. Independent WiFi upload: when on charge / hard-powered the device auto-joins WiFi and pushes recordings to generic cloud storage with no phone present. ## Components ### firmware (device) - Responsibility: capture audio, store it, manage power/controls, expose control + data over BLE and WiFi, and upload autonomously when powered. - Location: `firmware/` (PlatformIO, Arduino-ESP32, target ESP32-S3). - Modules (M1 landed: audio, storage, recorder, ux; rest planned per milestone): - `audio` - I2S/PDM mic capture presenting 16-bit PCM mono (ESP_I2S). [M1] - `storage`- microSD (FAT) streaming WAV writer + sidecar JSON metadata. [M1] - `recorder` - session state machine (idle/recording), file naming, metadata. [M1] - `ux` - button (short-press start/stop) + status LED (haptic later). [M1] - `power` - battery read (ADC), charge/VBUS detect -> mode switch. - `config` - NVS-stored settings (WiFi creds, upload target + keys, codec). - `net_wifi` - WiFi manager (join, reconnect), mDNS. - `api_http` - on-device REST server (see `api/openapi.yaml`). - `uploader` - S3-compatible / WebDAV client; pushes audio + metadata when powered. - `ble` - GATT: device info, battery, record control, WiFi provisioning, status. - `ota` - firmware update over HTTP. - Depends on: microSD, I2S mic, LiPo + charge IC (see `hardware/BOM.md`). - Why this way: ESP32-S3 has WiFi + BLE 5 + PSRAM + USB in one cheap chip, so all three sync paths and audio buffering fit on one board with off-the-shelf modules. ### server (self-hosted AI) - Responsibility: ingest recordings, transcribe, summarise, store, and serve the open API with exports. - Location: `server/` (FastAPI). - Pipeline: ingest (from cloud store or direct upload) -> store raw audio (object store) -> transcribe (faster-whisper) -> summarise (Ollama LLM) -> index metadata (DB) -> expose REST API + exports (audio, TXT, SRT, VTT, Markdown, JSON). - Depends on: object storage (MinIO or local FS), a DB (SQLite to start, Postgres later), faster-whisper, Ollama. All self-hostable. - Why this way: keeps the device cheap and low-power (no on-device AI); all heavy compute runs on hardware the user owns; every step swappable and open. ### app (Flutter) - Responsibility: provision the device, browse the library, play audio, show transcripts and summaries, export/share, manage settings. - Location: `app/`. - Depends on: device BLE + REST API (provisioning/transfer) and server REST API (library, transcripts, summaries). - Why this way: one codebase for Android + iOS. iOS restricts background BLE, so BLE is used for control/provisioning and WiFi for bulk transfer, which matches the design. ### case (3D print) - Responsibility: enclosure for the chosen board + battery + mic + button + USB + LED. - Location: `case/` (OpenSCAD, parametric). - Why this way: code-defined parametric model re-tunes to exact module dimensions and stays fully open and diffable. ### hardware - Responsibility: BOM, wiring/pinout, build notes. No custom PCB in v1. - Location: `hardware/`. ### api - Responsibility: the single source of truth for the open API (device + server). - Location: `api/openapi.yaml`. ## Data and state Recording metadata (sidecar JSON on device; row in server DB), canonical shape: ```json { "id": "rec_20260703T101500Z_ab12", "device_id": "openscribe-abc123", "started_at": "2026-07-03T10:15:00Z", "duration_s": 372.5, "sample_rate": 16000, "channels": 1, "codec": "wav_pcm_s16le", "size_bytes": 11920000, "sha256": "…", "source": "device", "sync_state": "local | uploaded | ingested | transcribed | summarised", "transcript_ref": null, "summary_ref": null } ``` - On device: files on microSD (`/recordings/.wav` + `.json`); config + secrets in NVS (never on the SD card in clear). - In transit: audio + metadata JSON uploaded to the configured object store; server ingests from there (or accepts direct upload). - On server: audio + artefacts (transcript, summary, subtitle files) in the object store; metadata + refs in the DB. ## External dependencies - ESP32-S3 (Espressif), Arduino-ESP32, PlatformIO - mature, free, WiFi + BLE + PSRAM. - faster-whisper (CTranslate2) - fast self-hosted STT, CPU or GPU. - Ollama - self-hosted local LLM runtime for summaries. - MinIO (or any S3-compatible / WebDAV target) - self-hosted object storage. - FastAPI, Flutter - open, well supported. All chosen to be self-hostable and open; no required proprietary SaaS. ## Constraints and trade-offs - Audio default is WAV PCM 16 kHz mono for simplicity and quality; larger files, so WiFi is the real transfer channel and Opus/ADPCM is a later size optimisation. - No on-device transcription: keeps the device cheap/low-power; needs the server for AI. - BLE bulk transfer is slow and iOS-restricted, so BLE only does control/provisioning and hands transfers to WiFi. - v1 uses off-the-shelf modules (no PCB): easier to build, bigger case than a Plaud. - Security: device REST API and config writes must be authenticated (token in NVS); independent uploads use scoped object-store credentials. Hardening tracked in TODO.