Implements the first working feature: the device records audio to the microSD
card, toggled by the button, with LED status and per-recording JSON metadata.
What changed:
- firmware/src/audio.{h,cpp}: mic capture via the core-bundled ESP_I2S. Dev board
uses I2S standard mode (INMP441/ICS-43434); XIAO uses PDM mode (onboard mic).
Presents 16-bit PCM mono to callers regardless of board.
- firmware/src/storage.{h,cpp}: microSD on a dedicated HSPI bus + a streaming
WavWriter that writes a 44-byte PCM header and patches RIFF/data sizes on close;
plus sidecar JSON metadata writer.
- firmware/src/recorder.{h,cpp}: idle/recording state machine; creates
/recordings/<id>.wav, pumps mic chunks in on update(), finalises + writes
<id>.json (Recording schema from api/openapi.yaml) on stop.
- firmware/src/ux.{h,cpp}: debounced button (short press toggles) + status LED
patterns (idle/recording/error), active-low aware.
- firmware/src/main.cpp: wires ux + recorder; loop toggles on button and drains
the mic while recording.
- firmware/include/audio_config.h: 16 kHz mono 16-bit, chunk size, rec dir.
- firmware/include/pins.h: added XIAO PDM mic + onboard SD pins, LED active-low flag.
- state/: TODO, ARCHITECTURE, NOTES updated for M1 and the deferred follow-ups.
Why:
- Recording is the foundation every later milestone (transfer, upload, transcription)
builds on. Kept dependency-free (only core-bundled ESP_I2S + SD) for simple CI builds.
Notes:
- Not compiled locally (no PlatformIO on the dev host) or hardware-verified; Forgejo
Actions CI builds both board profiles. Follow-ups tracked in state/TODO.md:
INMP441 16-bit level calibration, and real NTP timestamps (ids are uptime-based
until M2 brings WiFi/NTP).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
134 lines
6.3 KiB
Markdown
134 lines
6.3 KiB
Markdown
# Architecture
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> How the system is built and why. Update this when the structure changes; a change is
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> not finished until this reflects it.
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## Overview
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Four parts, connected by an open REST API and a shared recording data model:
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```
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[ Device: ESP32-S3 ] [ Self-hosted server ]
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mic -> I2S -> ring buffer (PSRAM) FastAPI
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-> encoder (WAV) -> microSD +-- ingest (from cloud store / upload)
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button/LED/haptic UX +-- faster-whisper (transcribe)
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power + charge detect +-- Ollama LLM (summarise)
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| BLE (control/provision) +-- object store (MinIO/local) + DB
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| WiFi REST API (LAN) `-- open REST API + exports
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| WiFi uploader (on charge) --> cloud store -----------^
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v v
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[ Flutter app: Android + iOS ] <---- open REST API (device + server)
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```
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Three sync paths, exactly as specified:
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1. BLE: control, status, and WiFi provisioning (small data). Portable/battery mode.
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2. WiFi to app: bulk recording transfer via the device REST API (fast).
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3. Independent WiFi upload: when on charge / hard-powered the device auto-joins WiFi and
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pushes recordings to generic cloud storage with no phone present.
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## Components
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### firmware (device)
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- Responsibility: capture audio, store it, manage power/controls, expose control + data
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over BLE and WiFi, and upload autonomously when powered.
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- Location: `firmware/` (PlatformIO, Arduino-ESP32, target ESP32-S3).
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- Modules (M1 landed: audio, storage, recorder, ux; rest planned per milestone):
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- `audio` - I2S/PDM mic capture presenting 16-bit PCM mono (ESP_I2S). [M1]
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- `storage`- microSD (FAT) streaming WAV writer + sidecar JSON metadata. [M1]
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- `recorder` - session state machine (idle/recording), file naming, metadata. [M1]
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- `ux` - button (short-press start/stop) + status LED (haptic later). [M1]
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- `power` - battery read (ADC), charge/VBUS detect -> mode switch.
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- `config` - NVS-stored settings (WiFi creds, upload target + keys, codec).
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- `net_wifi` - WiFi manager (join, reconnect), mDNS.
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- `api_http` - on-device REST server (see `api/openapi.yaml`).
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- `uploader` - S3-compatible / WebDAV client; pushes audio + metadata when powered.
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- `ble` - GATT: device info, battery, record control, WiFi provisioning, status.
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- `ota` - firmware update over HTTP.
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- Depends on: microSD, I2S mic, LiPo + charge IC (see `hardware/BOM.md`).
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- Why this way: ESP32-S3 has WiFi + BLE 5 + PSRAM + USB in one cheap chip, so all three
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sync paths and audio buffering fit on one board with off-the-shelf modules.
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### server (self-hosted AI)
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- Responsibility: ingest recordings, transcribe, summarise, store, and serve the open
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API with exports.
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- Location: `server/` (FastAPI).
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- Pipeline: ingest (from cloud store or direct upload) -> store raw audio (object store)
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-> transcribe (faster-whisper) -> summarise (Ollama LLM) -> index metadata (DB) ->
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expose REST API + exports (audio, TXT, SRT, VTT, Markdown, JSON).
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- Depends on: object storage (MinIO or local FS), a DB (SQLite to start, Postgres later),
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faster-whisper, Ollama. All self-hostable.
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- Why this way: keeps the device cheap and low-power (no on-device AI); all heavy compute
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runs on hardware the user owns; every step swappable and open.
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### app (Flutter)
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- Responsibility: provision the device, browse the library, play audio, show transcripts
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and summaries, export/share, manage settings.
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- Location: `app/`.
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- Depends on: device BLE + REST API (provisioning/transfer) and server REST API (library,
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transcripts, summaries).
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- Why this way: one codebase for Android + iOS. iOS restricts background BLE, so BLE is
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used for control/provisioning and WiFi for bulk transfer, which matches the design.
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### case (3D print)
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- Responsibility: enclosure for the chosen board + battery + mic + button + USB + LED.
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- Location: `case/` (OpenSCAD, parametric).
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- Why this way: code-defined parametric model re-tunes to exact module dimensions and
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stays fully open and diffable.
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### hardware
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- Responsibility: BOM, wiring/pinout, build notes. No custom PCB in v1.
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- Location: `hardware/`.
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### api
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- Responsibility: the single source of truth for the open API (device + server).
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- Location: `api/openapi.yaml`.
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## Data and state
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Recording metadata (sidecar JSON on device; row in server DB), canonical shape:
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```json
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{
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"id": "rec_20260703T101500Z_ab12",
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"device_id": "openscribe-abc123",
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"started_at": "2026-07-03T10:15:00Z",
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"duration_s": 372.5,
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"sample_rate": 16000,
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"channels": 1,
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"codec": "wav_pcm_s16le",
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"size_bytes": 11920000,
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"sha256": "…",
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"source": "device",
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"sync_state": "local | uploaded | ingested | transcribed | summarised",
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"transcript_ref": null,
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"summary_ref": null
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}
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```
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- On device: files on microSD (`/recordings/<id>.wav` + `<id>.json`); config + secrets in
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NVS (never on the SD card in clear).
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- In transit: audio + metadata JSON uploaded to the configured object store; server
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ingests from there (or accepts direct upload).
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- On server: audio + artefacts (transcript, summary, subtitle files) in the object store;
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metadata + refs in the DB.
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## External dependencies
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- ESP32-S3 (Espressif), Arduino-ESP32, PlatformIO - mature, free, WiFi + BLE + PSRAM.
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- faster-whisper (CTranslate2) - fast self-hosted STT, CPU or GPU.
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- Ollama - self-hosted local LLM runtime for summaries.
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- MinIO (or any S3-compatible / WebDAV target) - self-hosted object storage.
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- FastAPI, Flutter - open, well supported.
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All chosen to be self-hostable and open; no required proprietary SaaS.
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## Constraints and trade-offs
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- Audio default is WAV PCM 16 kHz mono for simplicity and quality; larger files, so WiFi
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is the real transfer channel and Opus/ADPCM is a later size optimisation.
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- No on-device transcription: keeps the device cheap/low-power; needs the server for AI.
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- BLE bulk transfer is slow and iOS-restricted, so BLE only does control/provisioning and
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hands transfers to WiFi.
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- v1 uses off-the-shelf modules (no PCB): easier to build, bigger case than a Plaud.
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- Security: device REST API and config writes must be authenticated (token in NVS);
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independent uploads use scoped object-store credentials. Hardening tracked in TODO.
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