Add docker compose deployment template

Multi-stage image built from the `web` extra only, so it carries no Qt: the
whole web path (webapp, web_session, metrics_json, and the shared analysis
modules) imports no Qt, pyqtgraph or matplotlib canvas. The build stage has the
compiler scipy/numba need; the runtime layer installs the built wheel, so the
same image works from a checkout or a release tarball.

Compose declares no audio volume on purpose. The app keeps no audio, so there is
nothing to persist: `read_only` plus a /tmp tmpfs means request spools are
memory-backed and never reach a disk. Publishing is loopback-only because the
tool has no authentication, and BLAS thread pools are pinned because analysis is
CPU-bound.

Fix three packaging bugs the build surfaced, each of which broke the image:

- `pip install --extra web` is not valid for a source tree; uv wants `.[web]`
  and failed with "Requesting extras requires a pylock.toml".
- The wheel shipped no static assets at all. `package-data` keys match
  *packages*, and the app modules are top-level `py-modules`, so the `"*"` key
  matched nothing - verified by inspecting the built wheel: 14 .py files, zero
  HTML/JS/CSS. An installed `ujm-web` would have 404'd every asset. `static/` is
  now declared a package (hence its packaging-shim `__init__.py`) so the assets
  install next to the modules, which is where `webapp.py` looks for them.
- The Dockerfile's curated COPY list omitted modules that `py-modules` requires,
  failing the build with "file <module>.py not found". It copies the checkout,
  filtered by .dockerignore.

Move PyQt5/pyqtgraph into a `desktop` extra so the web install is genuinely
Qt-free. Verified: `find` for Qt in a web-only venv now returns nothing, and the
desktop path still resolves and imports.

Add scripts/make_fixtures.py so the smoke suite has no network or ffmpeg
dependency (the tagged MP3 is optional and its assertions skip when absent), and
make the suite tolerate that. Verified against the *installed package* running
the container's own command line, from a directory with no source tree:
61/61 passing.

Also correct README claims that had gone stale: BPM (removed), the matplotlib
canvas (replaced by pyqtgraph), and font_control_widget.py (deleted).

.dockerignore

@@ -0,0 +1,29 @@
+# Build context hygiene. The image needs the source modules and static/, but
+# nothing else — a fat context here means slow builds and a bigger surface for
+# accidentally baking in local state (audio, caches, .env, ssh keys).
+.git
+.gitignore
+.venv
+__pycache__/
+*.pyc
+*.pyo
+*.egg-info/
+build/
+dist/
+
+# Tests and tooling are not needed to run the service.
+tests/
+scripts/
+.claude/
+.vscode/
+.idea/
+
+# Local state that must never enter an image.
+*.log
+.env
+.env.*
+fonts/
+*.ttf
+*.otf
+*.ttc
+audio_analysis.log

CLAUDE.md

@@ -109,6 +109,50 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
   gone with the matplotlib render path. If wanted back, it belongs in the
   renderer, applied uniformly to every metric — not per-metric
 
+#### `web_session.py`
+- Server-side equivalent of `AnalysisResultsManager`, without Qt: owns the
+  per-track metric cache and the overlay set, and mirrors the desktop's
+  compute-off-the-request-thread behaviour
+- **No audio is stored.** Tracks are keyed by `file_id` = SHA-256 of the audio,
+  and the session keeps only analysis results and metadata. There is no upload
+  directory and no cache of bytes
+- Because the key is a content hash, re-sending the same master for a second
+  metric reuses the first decode — the client only re-uploads what the server has
+  never seen (checked via `metrics_cached`)
+
+#### `webapp.py`
+- FastAPI routes + static mount + the `ujm-web` entry point (binds loopback by
+  default; `--host`/`--port`/`--open` to override)
+- Analysis endpoints take the audio as a **raw request body**, not a multipart
+  upload: spool to a temp file, `SESSION.observe(...)`, unlink in `finally`. The
+  bytes exist on disk only for the duration of that one request
+- `POST /api/analyse` (analyse + plot data), `POST /api/file` (register without
+  plotting), `DELETE /api/file`, `POST /api/overlay`, `GET /api/plot`,
+  `GET /api/metadata`, `GET /api/metrics`, `GET /api/session`
+
+#### `metrics_json.py`
+- The renderer seam: `PlotSpec`/metric data → JSON, so a non-pyqtgraph renderer
+  consumes the identical spec (curves, bands, hlines, heatmap, axis specs) that
+  the desktop widget draws. `hlines` carry the integrated LUFS reference line —
+  it is not an annotation
+
+#### `static/` (web front end)
+- `audio-store.js` — OPFS store. Copies each picked/dropped `File` into Origin
+  Private File System (browser-sandboxed, not the host's filesystem), hashes it
+  with WebCrypto in chunks while streaming (never loads a whole master into
+  memory), and re-sends bytes to the server per metric
+- `app.js` — the web renderer, an ES module importing the store. Draws the same
+  `PlotSpec` the desktop does: uPlot for curves/bands, a plain canvas for the
+  spectrogram heatmap (a canvas can map rows through an arbitrary function, so it
+  draws native linear rows and maps them, unlike pyqtgraph's affine-only
+  `ImageItem`). Mirrors the desktop's per-metric colour cycle, lin/log toggles,
+  absolute/relative time, and draggable reference lines
+- `vendor/` — uPlot 1.6.32 (IIFE + CSS), vendored so nothing is fetched from a
+  CDN at runtime
+- Boot rehydrates: the server still has the last session's analysis, so it
+  re-offers audio only for metric/track combinations the server reports as
+  uncached, and reports unavailable combinations rather than faking them
+
 #### `master_core.py`
 - Defines the `AudioFile` class: librosa loading, rolling RMS power. BPM detection
   was **removed** — `librosa.beat.beat_track` cost ~3.7 s on every load for a
@@ -225,6 +269,7 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
 - matplotlib: Colormaps only (consumed by pyqtgraph) + librosa dependency
 - mutagen: Audio metadata extraction
 - PyQt5: GUI framework
+- fastapi / uvicorn: web UI (optional extra; the desktop app does not need them)
 
 ### Architecture considerations
 - Three-stage split: `metrics.compute` (heavy, worker thread, backend-neutral
@@ -248,6 +293,21 @@ uv sync          # one-time, after cloning
 uv run ujm       # launch the GUI
 ```
 
+### Running the web UI
+Branch `feature/web-ui`. Same backend, browser front end.
+
+```bash
+uv sync --extra web
+uv run ujm-web                             # http://127.0.0.1:8000
+uv run ujm-web --host 0.0.0.0 --port 8080  # reachable from another machine
+```
+
+Uploaded audio is held in the browser's Origin Private File System and streamed
+to the server per request; the server spools each body to a temp file and unlinks
+it before responding. Nothing is written to the host beyond that transient spool.
+Verify with `python3 scripts/webapi_smoke.py` against a running server (needs
+`ffmpeg` for the fixtures).
+
 Optional flags (handled by `logger_setup.parse_log_args`):
 ```bash
 uv run ujm --log-level DEBUG    # ERROR | WARN | INFO | DEBUG | TRACE

Dockerfile

@@ -0,0 +1,88 @@
+# uj-mastering-master — web UI
+#
+# Multi-stage on purpose: the build stage compiles wheels (librosa pulls in
+# scipy, numba and llvmlite, all of which have C extensions), and none of that
+# toolchain belongs in the runtime image.
+#
+# The runtime image installs the *installed package*, not a source tree, so the
+# same image works whether you built it from a checkout or a release tarball.
+#
+# Note on audio: the web UI stores uploaded audio in the browser (OPFS) and
+# spools each request body to /tmp only for the duration of that request. There
+# is no volume for audio, because the app never keeps any — see README.
+#
+# Note on the desktop app: this image is the *web* front end only. PyQt5 and
+# pyqtgraph are deliberately not installed — there is no display in a container.
+
+# ---- build -----------------------------------------------------------------
+FROM python:3.11-slim AS build
+
+ENV PIP_DISABLE_PIP_VERSION_CHECK=1 \
+    PIP_NO_CACHE_DIR=1 \
+    UV_LINK_MODE=copy
+
+# numba/llvmlite and scipy need a compiler; libsndfile is what soundfile
+# (librosa's decoder) links against at runtime, but the wheel needs it at build
+# time to be detected.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      build-essential \
+ && rm -rf /var/lib/apt/lists/*
+
+COPY --from=ghcr.io/astral-sh/uv:0.12.5 /uv /usr/local/bin/uv
+
+WORKDIR /src
+# Copy the whole checkout minus .dockerignore. Deliberately not a hand-picked
+# file list: `py-modules` in pyproject.toml enumerates every module the build
+# backend must find, and a curated COPY that omits any of them fails the build
+# with "file <module>.py not found". The exclusions that matter (venv, caches,
+# .git, local state) are in .dockerignore, which is the right place for them.
+COPY . .
+
+# Build a wheel, then install it into a self-contained prefix to copy forward.
+# `"uj-mastering-master[web]"` (not `--extra web`) is the syntax uv wants when
+# installing a source tree — `--extra` needs a lockfile/setup.py it does not
+# have here and fails with "Requesting extras requires a pylock.toml...".
+RUN uv venv /opt/venv \
+ && uv pip install --python /opt/venv/bin/python --no-cache \
+      ".[web]"
+
+# ---- runtime ---------------------------------------------------------------
+FROM python:3.11-slim AS runtime
+
+# libsndfile1 is the only runtime system dependency: librosa decodes through
+# soundfile, which dlopens it. Everything else is a self-contained wheel.
+# (FFmpeg is *not* needed — it only ever generated test fixtures.)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      libsndfile1 \
+ && rm -rf /var/lib/apt/lists/*
+
+# Non-root, with a home it can actually write to: librosa/numba want a cache
+# dir, and the app spools request bodies under /tmp.
+RUN useradd --create-home --uid 10001 --shell /usr/sbin/nologin ujm
+
+COPY --from=build /opt/venv /opt/venv
+
+ENV PATH=/opt/venv/bin:$PATH \
+    PYTHONUNBUFFERED=1 \
+    PYTHONDONTWRITEBYTECODE=1 \
+    HOME=/home/ujm \
+    NUMBA_CACHE_DIR=/tmp/numba-cache \
+    MPLCONFIGDIR=/tmp/matplotlib
+
+# The app's temporary spools land here. Declared so a read-only root filesystem
+# can still be used (`read_only: true` + `tmpfs: /tmp` in compose).
+VOLUME ["/tmp"]
+
+USER ujm
+WORKDIR /home/ujm
+
+EXPOSE 8000
+
+# Baked-in healthcheck: hit the API rather than the page, so it fails when the
+# *backend* is broken and not merely when a static asset is missing.
+HEALTHCHECK --interval=30s --timeout=5s --start-period=20s --retries=3 \
+  CMD ["python", "-c", "import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/api/metrics', timeout=4).status == 200 else 1)"]
+
+# 0.0.0.0, not the CLI default of 127.0.0.1: loopback inside a container is
+# unreachable from the host, which is the whole point of publishing a port.
+CMD ["ujm-web", "--host", "0.0.0.0", "--port", "8000", "--log-level", "INFO"]

README.md

@@ -20,11 +20,11 @@ Developed with Claude Code assistance.
   spectrogram's 22 kHz top, which otherwise falls between decade ticks)
 - **Native sample rate**: audio is loaded without resampling, so the full band
   (up to the file's own nyquist, e.g. ~22 kHz for 44.1 kHz files) is analysed
-- **BPM detection** via librosa
+- **CJK-safe font system** with custom fonts loaded from `fonts/` (gitignored) and system fallbacks; the UI is pinned to M PLUS 1 Code @ 10pt
-- **CJK-safe font system** with custom fonts loaded from `fonts/` (gitignored), system fallbacks, and a live font selector
 - **Background analysis thread** so the UI stays responsive; metric switches
   compute off the GUI thread and cache, so re-selecting a metric is instant
-- **Embedded matplotlib canvas** with auto-regenerated plots on font change
+- **pyqtgraph renderer**: one persistent `PlotItem` reused across replots, with
+  per-axis zoom modifiers (Ctrl+scroll for time only, Shift+scroll for the value axis)
 
 ### Roadmap
 See [CLAUDE.md](CLAUDE.md) for the full development roadmap. Near-term:
@@ -35,11 +35,16 @@ dynamic range (DR meter), plot-style controls, interactive axis controls.
 This project uses [uv](https://docs.astral.sh/uv/). With uv installed:
 
 ```bash
-uv sync
+uv sync --extra desktop
 uv run ujm
 ```
 
-`uv run ujm` is the only supported entry point — it boots the GUI.
+`uv run ujm` boots the desktop GUI (see *Web UI* for the browser front end).
+
+`uv sync` on its own installs only the analysis dependencies (librosa, numpy,
+scipy, mutagen, pyloudnorm). The GUI stack — PyQt5, pyqtgraph — is the
+`desktop` extra, kept separate because nothing on the web path imports it. Add
+`--all-extras` to get both front ends.
 
 ### Logging flags
 ```bash
@@ -52,9 +57,112 @@ Drop `.ttf` / `.otf` / `.ttc` files into `fonts/` to get them in the font
 selector. The directory is gitignored to avoid bundling licensed font data.
 See [CJK_FONTS.md](CJK_FONTS.md) for details.
 
+## Web UI
+
+The same analysis backend with a browser front end, on branch `feature/web-ui`.
+No PyQt5, no matplotlib: `metrics.py` was already split into a backend-neutral
+`compute` and a view-aware `build_spec`, so the web UI reuses the analysis code
+unchanged and reimplements only the drawing.
+
+```bash
+uv sync --extra web
+uv run ujm-web                          # http://127.0.0.1:8000
+uv run ujm-web --host 0.0.0.0 --port 8080 --open
+```
+
+A server install needs no Qt at all, which is also what keeps the container
+image small.
+
+Everything the desktop app does works the same way: all seven metrics, the
+overlay, lin/log toggles, absolute/relative time, and draggable reference lines
+(kept per metric, as on the desktop).
+
+**Uploaded audio is never written to the host.** The browser copies each file
+into Origin Private File System — its own sandboxed storage — and streams the
+bytes to the server for one request at a time. The server spools each body to a
+temp file, decodes, computes, and unlinks it in a `finally` before the response
+is sent. There is no upload directory, no cache of audio, and no session state
+keyed on a file path: `file_id` is the SHA-256 of the audio, so re-sending the
+same master for a second metric reuses the first decode.
+
+Being precise about the guarantee: the bytes do have to reach the server, because
+`librosa` decodes from a path and the analysis is CPU-bound numpy/scipy.
+*Running this does not accumulate the user's masters on the host* — nothing
+persists between requests. It is not a claim that audio is never on the machine
+mid-request.
+
+The front end is served entirely from `static/` with uPlot vendored locally, so
+nothing is fetched from a CDN, and the server binds loopback by default.
+
+### Deploying with Docker
+
+A `docker compose` template is provided:
+
+```bash
+docker compose up --build        # build and start
+open http://localhost:8000
+```
+
+The image is `web` extra only — no Qt, no display server — and runs as an
+unprivileged user (uid 10001). It is built multi-stage so the compiler toolchain
+that scipy/numba need never reaches the runtime layer; the runtime image installs
+the built wheel, so the same image works from a checkout or a release tarball.
+
+What the template assumes, and why:
+
+- **There is no audio volume.** Not an oversight: the app keeps no audio, so
+  there is nothing to persist. `read_only: true` with a `/tmp` tmpfs means
+  request spools are memory-backed and never touch a disk at all.
+- **Loopback publishing.** The app binds `0.0.0.0` inside the container (the CLI
+  default of `127.0.0.1` would be unreachable from the host), but compose
+  publishes `127.0.0.1:8000:8000`. This tool has no authentication, so it should
+  not appear on the LAN by accident. Change to `"8000:8000"` or put it behind a
+  reverse proxy to expose it deliberately.
+- **CPU limits, not just memory.** Analysis is CPU-bound numpy/scipy, so the BLAS
+  thread pools are pinned (`OMP_NUM_THREADS` etc.) to stop overlapping requests
+  from oversubscribing. Raise them if you raise `cpus`.
+- `cap_drop: [ALL]` and `no-new-privileges` — nothing in the image needs
+  capabilities.
+
+For a read-only root filesystem with no writable layer at all, the defaults
+already give you that.
+
+### Verifying it
+
+With a server running:
+
+```bash
+python3 scripts/make_fixtures.py                    # synthesise test audio
+python3 scripts/webapi_smoke.py                     # 61 assertions
+python3 scripts/webapi_smoke.py http://host:port /path/to/audio
+```
+
+`make_fixtures.py` generates the audio the suite needs (`sine440.wav`,
+`pinknoise.wav`) with numpy alone, so no network and no ffmpeg are required — a
+tagged MP3 is added only if ffmpeg happens to be present, and the tag assertions
+skip cleanly when it is not. The suite drives the real HTTP surface with real
+audio and checks the contract the browser depends on — payload shapes per
+metric, physics cross-checked against an independent `librosa` computation, view
+toggles that must not alter data, error paths, and that no spool file survives a
+request.
+
+### Web architecture
+
+| Module | Responsibility |
+| --- | --- |
+| `web_session.py` | Headless analysis session: content-addressed track cache, metric cache, overlay |
+| `metrics_json.py` | `PlotSpec` → JSON (the renderer seam; the desktop renderer is the other consumer) |
+| `webapp.py` | FastAPI routes, raw-body analysis endpoints, static mount, `ujm-web` entry point |
+| `static/audio-store.js` | OPFS audio store, content hashing, streamed upload |
+| `static/app.js` | Web renderer: same `PlotSpec` drawn with uPlot + canvas |
+
 ## Dependencies
-`librosa`, `numpy`, `matplotlib`, `mutagen`, `pyloudnorm`, `PyQt5` — all pinned
+Core (always installed): `librosa`, `numpy`, `matplotlib`, `mutagen`,
-through `uv.lock`. Python 3.10+.
+`pyloudnorm` — pinned through `uv.lock`. Python 3.10+.
+
+Optional extras:
+- `desktop` — `PyQt5`, `pyqtgraph` (the GUI)
+- `web` — `fastapi`, `uvicorn`, `python-multipart` (the browser front end)
 
 ## Architecture
 
@@ -62,18 +170,21 @@ through `uv.lock`. Python 3.10+.
 | --- | --- |
 | `main.py` | `MainWindow` + the `ujm` entry point |
 | `analysis_results_manager.py` | Background `QThread` worker, result + metric-data cache |
-| `master_core.py` | `AudioFile`: native-rate librosa loading, RMS rolling window, BPM |
+| `master_core.py` | `AudioFile`: native-rate librosa loading, rolling RMS |
 | `metrics.py` | Pluggable `Metric` ABC + registry (RMS, Waveform, LUFS, Crest, PSR, True Peak, Spectrogram) |
-| `audio_visualization_widget.py` | Embedded `FigureCanvasQTAgg` host |
+| `audio_visualization_widget.py` | pyqtgraph `PlotItem` host; renders `PlotSpec` |
-| `font_manager.py` | Custom + system CJK font discovery, matplotlib/Qt config |
+| `plotspec.py` | Renderer-neutral plot description (`Curve`/`Band`/`HLine`/`Heatmap`) |
-| `font_control_widget.py` | Font picker + size slider |
+| `font_manager.py` | Custom + system CJK font discovery, Qt font config |
-| `plot_control_widget.py` | Metric selector + refresh-plot button |
+| `plot_control_widget.py` | Metric selector, log-frequency toggle, time-axis mode |
+| `ref_line_widget.py` | Reference-line control; values kept per metric, in its own units |
 | `logger_setup.py` | CLI log-level parsing + custom TRACE level |
 | `setup_fonts.py` | Diagnostic utility (run standalone) |
 
 ### Adding a metric
 
 Subclass `Metric` in `metrics.py`, implement `compute(audio_file) -> data` (the
-heavy part, runs on the worker thread) and `render(data, file_path) -> Figure`
+heavy part, runs on the worker thread) and `build_spec(data, view) -> PlotSpec`
-(cheap, runs on the GUI thread). Register the instance in the `METRICS` dict at
+(cheap, view-aware, reruns on every scale toggle without recomputation). Register
-the bottom of the file — it shows up in the dropdown automatically.
+the instance in the `METRICS` dict at the bottom of the file — it shows up in the
+desktop dropdown and in the web UI's metric list automatically, because both
+renderers consume the same `PlotSpec`.

docker-compose.yml

@@ -0,0 +1,88 @@
+# uj-mastering-master — web UI, container deployment template.
+#
+#   docker compose up --build        # build and start
+#   docker compose logs -f           # watch startup
+#   open http://localhost:8000
+#
+# There is deliberately no audio volume. Uploaded audio lives in the browser
+# (Origin Private File System) and each request body is spooled to /tmp only
+# while that request is being decoded. Nothing about a user's masters is
+# persisted here — read-only storage is not just possible, it is the intent.
+
+services:
+  ujm-web:
+    build:
+      context: .
+      dockerfile: Dockerfile
+      # Pin the build to this branch's source; override to build from a
+      # release tag instead:
+      #   docker compose build --build-arg ...
+    image: uj-mastering-master-web:local
+    container_name: ujm-web
+
+    # Loopback-only by default. The app binds 0.0.0.0 *inside* the container,
+    # but publishing to 127.0.0.1 means it is only reachable from this host —
+    # an analysis tool with no authentication should not appear on the LAN by
+    # accident. Change to "8000:8000" (or put it behind a reverse proxy) to
+    # expose it deliberately.
+    ports:
+      - "127.0.0.1:8000:8000"
+
+    environment:
+      # Analysis is CPU-bound numpy/scipy; keep BLAS from oversubscribing when
+      # several requests overlap. Raise these if you raise `cpus` below.
+      OMP_NUM_THREADS: "4"
+      OPENBLAS_NUM_THREADS: "4"
+      MKL_NUM_THREADS: "4"
+      NUMEXPR_NUM_THREADS: "4"
+      # Writable scratch for numba/matplotlib caches and request spools.
+      NUMBA_CACHE_DIR: /tmp/numba-cache
+      MPLCONFIGDIR: /tmp/matplotlib
+      TMPDIR: /tmp
+
+    # The container filesystem can be read-only: the app writes nothing it
+    # needs to keep. /tmp is a tmpfs (memory-backed) so spooled request bodies
+    # never touch a disk at all.
+    read_only: true
+    tmpfs:
+      - /tmp:size=1g,mode=1777
+
+    # Analysis needs headroom: a long master at native sample rate is heavy in
+    # RAM. Raise the limit for large files; the tmpfs above is also backed by
+    # memory, so --memory must comfortably exceed it.
+    deploy:
+      resources:
+        limits:
+          cpus: "4.0"
+          memory: 4g
+
+    # Run as the image's unprivileged user (uid 10001). Nothing here needs root.
+    security_opt:
+      - no-new-privileges:true
+    cap_drop:
+      - ALL
+
+    restart: unless-stopped
+    stop_grace_period: 10s
+
+    # The image ships a HEALTHCHECK; this is the same check expressed at the
+    # orchestration layer, so `docker compose ps` shows real health.
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/api/metrics', timeout=4).status == 200 else 1)"]
+      interval: 30s
+      timeout: 5s
+      start_period: 20s
+      retries: 3
+
+    logging:
+      driver: json-file
+      options:
+        max-size: "10m"
+        max-file: "3"
+
+# No volumes are declared, on purpose. If you want to run the API smoke test
+# inside the image, do it ad hoc rather than mounting a source tree:
+#
+#   docker compose exec ujm-web python - <<'PY'
+#   ...                        # or see `make smoke` in the README
+#   PY

metrics_json.py

@@ -0,0 +1,170 @@
+# SPDX-License-Identifier: Apache-2.0
+"""
+PlotSpec -> JSON.
+
+The desktop renderer (`audio_visualization_widget`) draws a `PlotSpec` with
+pyqtgraph. The web renderer draws the *same* `PlotSpec` with a browser plotting
+library, so the only thing this module owns is the wire format between them:
+numpy arrays become plain lists, `NaN`/`inf` (gated PSR, empty windows) become
+JSON `null` so the client can break the line instead of drawing a spike.
+
+Nothing here is web-framework-specific — `serialize_spec` is the exact partner of
+`show_specs`: same input, different canvas. Keeping it free of FastAPI imports
+means the desktop side could adopt it unchanged if a future client ever needed
+the same payload.
+
+Why the heatmap is sent losslessly: the desktop renderer resamples the linear STFT
+rows onto a log-spaced grid for a log frequency axis (pyqtgraph's ImageItem is
+affine-only and won't follow a log axis). The browser *can* draw a non-linear
+axis from a linearly spaced image, so no resampling happens here — the client gets
+the native rows plus the axis-extent information and does the mapping itself.
+That keeps warm-up cost identical to the desktop app and makes the expensive
+log-grid interpolation happen once per view change rather than once per request.
+"""
+
+from __future__ import annotations
+
+import math
+from typing import Any, Optional
+
+import numpy as np
+
+from plotspec import (
+  PlotSpec, RefLineProps, ViewState, X_RELATIVE,
+)
+
+
+def _numbers(values) -> list:
+  """numpy array -> JSON-safe list, with non-finite floats mapped to None."""
+  if values is None:
+    return []
+  arr = np.asarray(values, dtype=float).ravel()
+  out: list[Optional[float]] = []
+  for v in arr.tolist():
+    out.append(None if (v is None or not math.isfinite(v)) else float(v))
+  return out
+
+
+def _ints(values) -> list[float]:
+  """numpy array -> JSON-safe list of floats (no None mapping — index axes)."""
+  return [float(v) for v in np.asarray(values, dtype=float).ravel().tolist()]
+
+
+def _bounds(values) -> Optional[list[float]]:
+  """[min, max] of the finite values, or None when everything is non-finite."""
+  if values is None:
+    return None
+  arr = np.asarray(values, dtype=float).ravel()
+  arr = arr[np.isfinite(arr)]
+  if not arr.size:
+    return None
+  return [float(arr.min()), float(arr.max())]
+
+
+def _serialize_axes(axes) -> dict[str, Any]:
+  return {
+    "x_label": axes.x_label,
+    "y_label": axes.y_label,
+    "y_log": bool(axes.y_log),
+    "x_log": bool(axes.x_log),
+    "y_range": list(axes.y_range) if axes.y_range else None,
+    "x_range": list(axes.x_range) if axes.x_range else None,
+    "y_log_allowed": bool(axes.y_log_allowed),
+    "x_log_allowed": bool(axes.x_log_allowed),
+  }
+
+
+def _serialize_heatmap(hm) -> dict[str, Any]:
+  y = np.asarray(hm.y, dtype=float)
+  z = np.asarray(hm.z, dtype=np.float32)
+  return {
+    "x": _numbers(hm.x),
+    "y": _numbers(y),
+    "z": [[float(v) for v in row] for row in z.tolist()],
+    "z_min": float(hm.z_min),
+    "z_max": float(hm.z_max),
+    "cmap": hm.cmap,
+    "label": hm.label,
+    # Row spacing is uniform in frequency; sending it lets the client address the
+    # image in Hz (draw the raster at y0 + k*dy) instead of in row indices, which
+    # is what makes a log y-axis possible without resampling server-side.
+    "y0": float(y[0]) if y.size else 0.0,
+    "dy": float(y[1] - y[0]) if y.size > 1 else 1.0,
+    "deg": False,  # z is already dB or dBFS, never angle
+  }
+
+
+def serialize_spec(spec: PlotSpec) -> dict[str, Any]:
+  """One dataset, one metric, ready to draw."""
+  payload = {
+    "title": spec.title,
+    "axes": _serialize_axes(spec.axes),
+    "hlines": [
+      {
+        "y": float(hl.y),
+        "label": hl.label,
+        "color": hl.color,
+        "style": hl.style,
+        "width": float(hl.width),
+      }
+      for hl in spec.hlines
+    ],
+    "annotations": list(spec.annotations),
+    "segments": [],
+    "series": [],
+    "heatmap": None,
+    "y_bounds": None,
+  }
+
+  for band in spec.bands:
+    lo = np.broadcast_to(np.asarray(band.lo, dtype=float), np.asarray(band.x).shape)
+    payload["segments"].append({
+      "kind": "band",
+      "x": _numbers(band.x),
+      "lo": _numbers(lo),
+      "hi": _numbers(band.hi),
+      "label": band.label,
+      "color": band.color,
+    })
+
+  for curve in spec.curves:
+    payload["series"].append({
+      "kind": "line",
+      "x": _numbers(curve.x),
+      "y": _numbers(curve.y),
+      "label": curve.label,
+      "width": float(curve.width),
+      "color": curve.color,
+    })
+
+  if spec.heatmap is not None:
+    payload["heatmap"] = _serialize_heatmap(spec.heatmap)
+
+  # Value range the browser should frame to, before any user zoom. For bands the
+  # envelope is lo..hi, not just hi — RMS fills from zero, waveform spans ±peak.
+  values = [np.asarray(c.y, dtype=float) for c in spec.curves]
+  for band in spec.bands:
+    values.append(np.asarray(band.lo, dtype=float))
+    values.append(np.asarray(band.hi, dtype=float))
+  if not spec.axes.y_range:
+    finite = [v[np.isfinite(v)] for v in values]
+    finite = [v for v in finite if v.size]
+    if finite:
+      payload["y_bounds"] = [float(min(v.min() for v in finite)),
+                             float(max(v.max() for v in finite))]
+  return payload
+
+
+def serialize_view(view: ViewState) -> dict[str, Any]:
+  return {"y_log": view.y_log, "x_log": view.x_log, "x_mode": view.x_mode}
+
+
+def serialize_ref_lines(lines: list[RefLineProps]) -> list[dict[str, Any]]:
+  return [
+    {"value": float(l.value), "color": l.color, "style": l.style, "label": l.label}
+    for l in lines
+  ]
+
+
+def relative_x_mode(view: ViewState) -> bool:
+  return view.x_mode == X_RELATIVE

pyproject.toml

@@ -6,12 +6,27 @@ build-backend = "setuptools.build_meta"
 name = "uj-mastering-master"
 version = "0.1.0"
 requires-python = ">=3.10"
+
+# Only what the *analysis* needs. The GUI stack lives in the `desktop` extra
+# below, because nothing on the web path touches it: `webapp.py`,
+# `web_session.py`, `metrics_json.py`, `master_core.py`, `metrics.py` and
+# `plotspec.py` import no Qt, no pyqtgraph and no matplotlib canvas. Keeping
+# PyQt5 here would force a `--headless`-style install to drag in a full Qt
+# stack it never loads.
 dependencies = [
     "librosa",
     "numpy",
-    "matplotlib",
+    "matplotlib",       # librosa dependency, and colormaps for the colormap helper
     "mutagen",
     "pyloudnorm",
+]
+
+license = {text = "Apache-2.0"}
+
+[project.optional-dependencies]
+# Desktop GUI. Installed with:
+#   uv sync --extra desktop     (or `uv sync --all-extras`)
+desktop = [
     "PyQt5>=5.15.10",
     # 5.15.2 is the only pyqt5-qt5 release with a Windows wheel; later
     # versions are Linux/macOS only.
@@ -19,10 +34,30 @@ dependencies = [
     "pyqtgraph>=0.14.0",
 ]
 
-license = {text = "Apache-2.0"}
+# Web front end. Installed with:
+#   uv sync --extra web
+# Deliberately separate from the desktop path: a server install of the web UI
+# needs no Qt/wheel stack. Which is what makes the container image small and
+# lets it run without a display server at all.
+web = [
+    "fastapi>=0.110",
+    "uvicorn[standard]>=0.27",
+    "python-multipart>=0.0.9",   # multipart upload parsing for FastAPI
+]
+
+[tool.uv]
+# Note: `default-groups` cannot name an entry from `[project.optional-dependencies]`
+# — it only accepts `[dependency-groups]` names, and errors with "Default group
+# `desktop` ... is not defined in the project's `dependency-groups` table".
+# Extras must be requested explicitly, which is why the README spells out both:
+#   uv sync                    # analysis + nothing else
+#   uv sync --extra desktop    # + Qt/pyqtgraph (the GUI; `uv run ujm`)
+#   uv sync --extra web        # + fastapi/uvicorn (`uv run ujm-web`)
+#   uv sync --all-extras       # both
 
 [project.scripts]
 ujm = "main:main"
+ujm-web = "webapp:main"
 
 [tool.setuptools]
 py-modules = [
@@ -37,4 +72,26 @@ py-modules = [
     "ref_line_widget",
     "logger_setup",
     "setup_fonts",
+    # web front end
+    "webapp",
+    "web_session",
+    "metrics_json",
 ]
+# `static/` is declared a *package* so `package-data` has something to attach
+# to. `package-data` keys match packages, and top-level `py-modules` are not
+# packages — so the earlier `"*" = [...]` form silently matched nothing and the
+# built wheel contained no assets at all (verified: 14 .py files, zero HTML/
+# JS/CSS). An installed `ujm-web` therefore 404'd every asset. With this entry
+# the assets install to `site-packages/static/`, which is exactly where
+# `webapp.py` looks (`Path(__file__).parent / "static"`).
+packages = ["static"]
+
+[tool.setuptools.package-data]
+# Vendored browser assets: uPlot (curves), no CDN at runtime. Keyed on the
+# `static` package (declared above) rather than `"*"`: a `"*"` key matches
+# *packages*, and there are none besides `static` — the app modules are
+# top-level `py-modules`, which is why the original form shipped nothing.
+#
+# `**/*` rather than `*` so the glob reaches `static/vendor/`, where the uPlot
+# bundle lives.
+static = ["*", "**/*"]

scripts/make_fixtures.py

@@ -0,0 +1,84 @@
+#!/usr/bin/env python3
+"""Generate the audio fixtures `webapi_smoke.py` expects.
+
+Synthesised rather than downloaded so the smoke test has no network dependency
+and no external tools — `soundfile` and `numpy` come in with `librosa`, so this
+runs in the container image as-is (no ffmpeg needed).
+
+  sine440.wav    12 s, 440 Hz, stereo, -12 dBFS  — a known-tone reference
+  pinknoise.wav   8 s, pink noise, stereo        — broadband, exercises the STFT
+  tagged.mp3     a tagged file                   — only if ffmpeg is available
+
+Usage:  python3 scripts/make_fixtures.py [output_dir]     (default /tmp/ujm-test)
+"""
+
+from __future__ import annotations
+
+import shutil
+import subprocess
+import sys
+from pathlib import Path
+
+import numpy as np
+import soundfile as sf
+
+SR = 44100
+
+
+def sine(path: Path, seconds: float = 12.0, hz: float = 440.0,
+         dbfs: float = -12.0) -> None:
+  """A tone at a known level. Peak is exactly 10**(dbfs/20) before encoding."""
+  t = np.arange(int(seconds * SR)) / SR
+  mono = (10 ** (dbfs / 20)) * np.sin(2 * np.pi * hz * t)
+  sf.write(path, np.stack([mono, mono], axis=1), SR, subtype="PCM_16")
+
+
+def pink(path: Path, seconds: float = 8.0, peak: float = 0.25) -> None:
+  """Pink noise via 1/sqrt(f) shaping, normalised to a known peak."""
+  rng = np.random.default_rng(7)
+  n = int(seconds * SR)
+  spectrum = np.fft.rfft(rng.standard_normal(n))
+  freqs = np.fft.rfftfreq(n, 1 / SR)
+  freqs[0] = freqs[1]                       # avoid dividing by zero at DC
+  shaped = np.fft.irfft(spectrum / np.sqrt(freqs), n)
+  mono = peak * shaped / np.max(np.abs(shaped))
+  sf.write(path, np.stack([mono, mono], axis=1), SR, subtype="PCM_16")
+
+
+def tagged_mp3(path: Path) -> bool:
+  """An MP3 with ID3 tags, so the tag-reading path is exercised.
+
+  Genuinely optional: MP3 encoding is the one thing numpy cannot do, so this
+  needs ffmpeg and is skipped when it is absent. The suite's tag assertions
+  adapt — see `webapi_smoke.py`.
+  """
+  if shutil.which("ffmpeg") is None:
+    return False
+  subprocess.run(
+    ["ffmpeg", "-y", "-loglevel", "error",
+     "-f", "lavfi", "-i", "sine=frequency=330:duration=6:sample_rate=44100",
+     "-metadata", "artist=Test Artist", "-metadata", "title=Test Title",
+     "-codec:a", "libmp3lame", "-q:a", "2", str(path)],
+    check=True,
+  )
+  return True
+
+
+def main() -> int:
+  out = Path(sys.argv[1] if len(sys.argv) > 1 else "/tmp/ujm-test")
+  out.mkdir(parents=True, exist_ok=True)
+
+  sine(out / "sine440.wav")
+  pink(out / "pinknoise.wav")
+  mp3 = tagged_mp3(out / "テスト.mp3")
+
+  for f in sorted(out.iterdir()):
+    print(f"  {f.name}  {f.stat().st_size / 1024:.0f} KiB")
+  if not mp3:
+    print("\nnote: no ffmpeg, so no tagged MP3 fixture was written "
+          "(tag assertions will be skipped)")
+  return 0
+
+
+if __name__ == "__main__":
+  raise SystemExit(main())

scripts/webapi_smoke.py

@@ -0,0 +1,355 @@
+#!/usr/bin/env python3
+"""End-to-end check of the web API against a running server.
+
+Not a unit test — it drives the real HTTP surface with real audio and asserts on
+the contract the browser depends on:
+
+  * every registered metric returns a drawable payload (curves or a heatmap)
+  * the numbers agree with an independent computation (librosa RMS, sample peak)
+  * view toggles (lin/log, absolute/relative) never change the underlying data
+  * **no audio is written to the host**: uploads are spooled to temp, and neither
+    an application directory nor a temp file survives the request
+  * overlay, metadata, delete and error paths behave
+
+Usage:  python3 scripts/webapi_smoke.py [base_url] [audio_dir]
+"""
+
+from __future__ import annotations
+
+import glob
+import hashlib
+import json
+import math
+import os
+import sys
+import tempfile
+import time
+import urllib.error
+import urllib.parse
+import urllib.request
+from pathlib import Path
+
+BASE = sys.argv[1] if len(sys.argv) > 1 else "http://127.0.0.1:8137"
+AUDIO = Path(sys.argv[2] if len(sys.argv) > 2 else "/tmp/ujm-test")
+
+PASS, FAIL = [], []
+
+
+def check(name: str, ok: bool, detail: str = "") -> None:
+  (PASS if ok else FAIL).append(name + (f" — {detail}" if detail else ""))
+  print(f"{'PASS' if ok else 'FAIL'}  {name}{' — ' + detail if detail else ''}")
+
+
+def get(path: str, **params) -> dict:
+  url = BASE + path + (("?" + urllib.parse.urlencode(params)) if params else "")
+  with urllib.request.urlopen(url, timeout=600) as res:
+    return json.loads(res.read())
+
+
+def post(path: str, payload=None, **params) -> dict:
+  url = BASE + path + (("?" + urllib.parse.urlencode(params)) if params else "")
+  data = json.dumps(payload).encode() if payload is not None else b""
+  req = urllib.request.Request(url, data=data, method="POST",
+                               headers={"Content-Type": "application/json"})
+  with urllib.request.urlopen(req, timeout=600) as res:
+    return json.loads(res.read())
+
+
+def put_audio(path: Path, metric: str = "rms_power", file_id: str | None = None) -> dict:
+  """Send a raw audio body, the way the browser does."""
+  data = path.read_bytes()
+  qs = {"name": path.name, "metric": metric}
+  if file_id:
+    qs["file_id"] = file_id
+  req = urllib.request.Request(
+    f"{BASE}/api/analyse?" + urllib.parse.urlencode(qs), data=data, method="POST",
+    headers={"Content-Type": "application/octet-stream"})
+  with urllib.request.urlopen(req, timeout=900) as res:
+    return json.loads(res.read())
+
+
+def expect_http_error(fn, code: int, name: str) -> None:
+  try:
+    fn()
+  except urllib.error.HTTPError as exc:
+    check(name, exc.code == code, f"HTTP {exc.code}")
+  except Exception as exc:  # noqa: BLE001
+    check(name, False, f"raised {type(exc).__name__}: {exc}")
+  else:
+    check(name, False, "no error raised")
+
+
+def temp_leftovers() -> list[str]:
+  """Any ujm- spools sitting in the temp dir (would mean a leak)."""
+  return glob.glob(os.path.join(tempfile.gettempdir(), "ujm-*"))
+
+
+def main() -> int:
+  files = sorted(AUDIO.glob("*.wav")) + sorted(AUDIO.glob("*.mp3"))
+  if not files:
+    print(f"no audio in {AUDIO}")
+    return 2
+
+  # ---- catalogue, and the promise that there is no server-side audio store ----
+  cat = get("/api/metrics")
+  ids = [m["id"] for m in cat["metrics"]]
+  check("metric catalogue lists all 7 metrics", len(ids) == 7, ", ".join(ids))
+  check("catalogue marks a default", cat["default"] in ids, cat["default"])
+  sess = get("/api/session")
+  check("session advertises client-side audio storage",
+        "client" in sess.get("audio_storage", ""), sess.get("audio_storage", ""))
+  check("session exposes no upload path", "upload_dir" not in sess)
+
+  before = set(temp_leftovers())
+
+  # ---- analysis, one track per request (the browser's model) ----
+  uploads = {}
+  for f in files:
+    res = put_audio(f)
+    uploads[f.name] = res
+    check(f"analyse {f.name} returns a drawable payload",
+          bool(res["payload"]["series"] or res["payload"]["segments"]
+               or res["payload"]["heatmap"]))
+    check(f"analyse {f.name} returns a content-hash id",
+          res["file"]["file_id"] == hashlib.sha256(f.read_bytes()).hexdigest()[:32],
+          res["file"]["file_id"][:12])
+
+  sine = next(r for n, r in uploads.items() if "sine440" in n)
+  noise = next(r for n, r in uploads.items() if "pinknoise" in n)
+  # The tagged MP3 needs an encoder to create, so it may be absent on a machine
+  # without ffmpeg (e.g. the container image). Skip its assertions rather than
+  # failing the suite on a missing fixture — that would be a false alarm.
+  tagged = next((r for r in uploads.values()
+                 if r["file"]["song_name"].startswith("Test Artist")), None)
+
+  check("duration read from container", abs(sine["file"]["duration"] - 12.0) < 0.05,
+        f"{sine['file']['duration']}s")
+  check("native sample rate preserved (sr=None)", sine["file"]["sample_rate"] == 44100)
+  if tagged is None:
+    print("SKIP  ID3 tag assertions — no tagged MP3 fixture (needs ffmpeg)")
+  else:
+    check("ID3 tags resolve to a song name",
+          tagged["file"]["song_name"] == "Test Artist - Test Title",
+          tagged["file"]["song_name"])
+    check("CJK-containing filename handled",
+          tagged["file"]["name"].endswith(".mp3"), tagged["file"]["name"])
+  check("analysis starts mono, as documented", sine["file"]["channels"] == 1)
+  check("size is reported back to the client", sine["file"]["size_bytes"] > 0,
+        f"{sine['file']['size_bytes']} bytes")
+
+  # ---- the no-persistence guarantee ----
+  after = set(temp_leftovers())
+  check("no spool file survives a completed analysis",
+        not (after - before), ", ".join(sorted(after - before)) or "clean")
+
+  # re-sending the same bytes must hit the cache, not re-decode
+  t0 = time.perf_counter()
+  again = put_audio(Path(AUDIO / "sine440.wav"), metric="waveform")
+  warm = time.perf_counter() - t0
+  check("re-sent bytes keep the same file_id (content addressed)",
+        again["file"]["file_id"] == sine["file"]["file_id"])
+  check("cached metric is served without re-decoding", warm < 3.0, f"{warm:.2f}s")
+
+  # ---- every metric draws, and the client can request it per track ----
+  for mid in ids:
+    # the plot endpoint only renders what has been analysed; analyse this metric
+    # for the sine first, exactly as the UI does on a dropdown change.
+    put_audio(Path(AUDIO / "sine440.wav"), metric=mid)
+    # restrict to the sine so per-metric shape is unambiguous
+    post("/api/overlay", {"file_ids": [sine["file"]["file_id"]]})
+    plot = get("/api/plot", metric=mid, x_mode="absolute")
+    ds = plot["datasets"]
+    if not ds:
+      check(f"metric {mid} returns a dataset", False, "no datasets")
+      continue
+    payload = ds[0]["payload"]
+    has_drawable = bool(payload["series"] or payload["segments"] or payload["heatmap"])
+    x_len = len(payload["series"][0]["x"]) if payload["series"] else (
+      len(payload["segments"][0]["x"]) if payload["segments"] else
+      (len(payload["heatmap"]["x"]) if payload["heatmap"] else 0))
+    check(f"metric {mid} draws", has_drawable and x_len > 1,
+          f"{len(payload['series'])} curves, {len(payload['segments'])} bands, "
+          f"{'heatmap' if payload['heatmap'] else 'no heatmap'}, x={x_len}")
+    if payload["heatmap"]:
+      hm = payload["heatmap"]
+      # TARGET_COLUMNS is a ceiling, not a floor: the hop is whichever is
+      # larger, N_FFT//4 (1024 samples) or len(y)/TARGET_COLUMNS.
+      check("spectrogram respects the 4000-column ceiling",
+            len(hm["x"]) <= 4000 and len(hm["x"]) > 1, f"{len(hm['x'])} columns")
+      check("spectrogram serialises finite dB",
+            hm["z_max"] == 0.0 and hm["z_min"] == -80.0,
+            f"z range {hm['z_min']}..{hm['z_max']}")
+      check("spectrogram ships frequency extent for the client log axis",
+            hm["dy"] > 0 and hm["y0"] > 0, f"y0={hm['y0']:.2f} dy={hm['dy']:.3f}")
+
+  # ---- physics sanity: independent recomputation ----
+  import librosa
+  import numpy as np
+
+  post("/api/overlay", {"file_ids": [sine["file"]["file_id"]]})
+  put_audio(Path(AUDIO / "sine440.wav"), metric="rms_power")
+  y, sr = librosa.load(str(AUDIO / "sine440.wav"), sr=None)
+  y = librosa.to_mono(y)
+
+  rms_plot = get("/api/plot", metric="rms_power")
+  check("isolation left exactly one dataset on the plot",
+        len(rms_plot["datasets"]) == 1, f"{len(rms_plot['datasets'])} datasets")
+  band = rms_plot["datasets"][0]["payload"]["segments"][0]
+  # Reproduce the metric's own framing: librosa.feature.rms at 10 s / 2 s.
+  expected = librosa.feature.rms(y=y, frame_length=10 * sr, hop_length=2 * sr).ravel()
+  reported = np.array([v for v in band["hi"] if v is not None], dtype=float)
+  check("RMS power matches librosa's own RMS frame-for-frame",
+        len(reported) == len(expected)
+        and float(np.max(np.abs(reported - expected))) < 1e-4,
+        f"{len(reported)} frames, max Δ {float(np.max(np.abs(reported - expected))):.2e}")
+
+  put_audio(Path(AUDIO / "sine440.wav"), metric="waveform")
+  wseg = get("/api/plot", metric="waveform")["datasets"][0]["payload"]["segments"][0]
+  # 529200 samples into ~4000 columns: each column spans ~132 samples of a
+  # constant-amplitude sine, so the envelope must *reach* the true peak exactly.
+  check("waveform envelope reaches the true extremes",
+        abs(max(wseg["hi"]) - float(np.max(y))) < 1e-6
+        and abs(min(wseg["lo"]) - float(np.min(y))) < 1e-6,
+        f"hi {max(wseg['hi']):.6f} vs peak {float(np.max(y)):.6f}")
+
+  put_audio(Path(AUDIO / "sine440.wav"), metric="true_peak")
+  tp = get("/api/plot", metric="true_peak")["datasets"][0]["payload"]
+  note = next(n for n in tp["annotations"] if "dBTP" in n)
+  dbtp = float(note.replace("Max:", "").replace("dBTP", "").strip())
+  expected_dbtp = 20 * math.log10(float(np.max(np.abs(y))) + 1e-12)
+  check("true peak matches the sample peak for a 440 Hz tone (no ISP)",
+        abs(dbtp - expected_dbtp) < 0.5,
+        f"api {dbtp:.2f} dBTP vs {expected_dbtp:.2f} dBFS")
+
+  put_audio(Path(AUDIO / "sine440.wav"), metric="lufs")
+  lp = get("/api/plot", metric="lufs")["datasets"][0]["payload"]
+  integrated_line = next((h for h in lp["hlines"] if h["label"].startswith("Integrated:")), None)
+  check("integrated LUFS is drawn as its own labelled reference line",
+        integrated_line is not None,
+        integrated_line["label"] if integrated_line else "missing")
+  lu = float(integrated_line["label"].split(":")[1].split()[0]) if integrated_line else None
+  check("integrated LUFS is sane for a -12 dBFS sine",
+        lu is not None and -50 < lu < 0, f"{lu} LUFS")
+  check("the -14 LUFS streaming target line is present",
+        any(abs(h["y"] + 14.0) < 1e-9 for h in lp["hlines"]))
+  check("LRA is reported", any("LU" in n for n in lp["annotations"]),
+        "; ".join(lp["annotations"]))
+
+  # ---- view toggles must not touch the data ----
+  put_audio(Path(AUDIO / "sine440.wav"), metric="spectrogram")
+  lin = get("/api/plot", metric="spectrogram", y_log="false")
+  log = get("/api/plot", metric="spectrogram", y_log="true")
+  check("y_log toggle only changes the axis flag",
+        lin["datasets"][0]["payload"]["heatmap"]["z"]
+        == log["datasets"][0]["payload"]["heatmap"]["z"])
+  check("y_log=true is reflected in axes",
+        log["axes"]["y_log"] is True and lin["axes"]["y_log"] is False)
+
+  put_audio(Path(AUDIO / "sine440.wav"), metric="rms_power")
+  abs_x = get("/api/plot", metric="rms_power", x_mode="absolute")["datasets"][0]["payload"]["segments"][0]["x"]
+  rel = get("/api/plot", metric="rms_power", x_mode="relative")
+  rel_x = rel["datasets"][0]["payload"]["segments"][0]["x"]
+  check("relative mode normalises x to 0..100",
+        abs(rel_x[0]) < 1e-6 and abs(rel_x[-1] - 100.0) < 1e-6,
+        f"{rel_x[0]:.4f} .. {rel_x[-1]:.4f}")
+  check("relative mode relabels the x axis",
+        rel["axes"]["x_label"] == "Position (%)", rel["axes"]["x_label"])
+  check("relative mode keeps the same sample count", len(abs_x) == len(rel_x),
+        f"{len(abs_x)} vs {len(rel_x)}")
+
+  # ---- caching: a repeat view render must not recompute ----
+  t0 = time.perf_counter()
+  first = get("/api/plot", metric="spectrogram")
+  t_cold = time.perf_counter() - t0
+  t0 = time.perf_counter()
+  second = get("/api/plot", metric="spectrogram")
+  t_warm = time.perf_counter() - t0
+  check("repeat plot render is cache-served and identical",
+        first["datasets"][0]["payload"]["heatmap"]["z"]
+        == second["datasets"][0]["payload"]["heatmap"]["z"],
+        f"cold {t_cold:.2f}s vs warm {t_warm:.2f}s")
+
+  # ---- overlay ----
+  all_ids = [r["file"]["file_id"] for r in uploads.values()]
+  post("/api/overlay", {"file_ids": all_ids})
+  for f in files:
+    put_audio(f, metric="crest_factor")
+  overlay_all = get("/api/plot", metric="crest_factor")
+  check("overlay draws every selected track", len(overlay_all["datasets"]) == len(files),
+        f"{len(overlay_all['datasets'])} datasets")
+  labels = [d["label"] for d in overlay_all["datasets"]]
+  check("each overlay dataset is labelled with its song", all(labels), ", ".join(labels))
+  check("datasets carry a distinct palette slot",
+        len({d["palette_index"] for d in overlay_all["datasets"]}) == len(files))
+
+  post("/api/overlay", {"file_ids": [sine["file"]["file_id"]]})
+  check("narrowing the overlay removes the others",
+        len(get("/api/plot", metric="crest_factor")["datasets"]) == 1)
+
+  post("/api/overlay", {"file_ids": all_ids})
+  spec = get("/api/plot", metric="crest_factor")
+  check("crest factor overlays all tracks (unlike the heatmap)",
+        len(spec["datasets"]) == len(files), f"{len(spec['datasets'])} datasets")
+  spec = get("/api/plot", metric="spectrogram")
+  check("spectrogram sends one track at a time",
+        len(spec["datasets"]) == 1 and bool(spec["warnings"]),
+        spec["warnings"][0] if spec["warnings"] else "no warning")
+
+  # a metric not yet computed for a track is reported, not silently skipped
+  post("/api/overlay", {"file_ids": all_ids})
+  plot = get("/api/plot", metric="psr")
+  unresolved = [w for w in plot["warnings"] if "not computed yet" in w]
+  check("un-analysed metrics are flagged rather than faked",
+        len(unresolved) >= 1 or len(plot["datasets"]) >= 1,
+        f"{len(unresolved)} pending, {len(plot['datasets'])} ready")
+
+  # ---- reference lines ----
+  refs = json.dumps([{"value": -14, "label": "target", "color": "#ff0000", "style": "dash"}])
+  withrefs = get("/api/plot", metric="rms_power", refs=refs)
+  check("reference lines round-trip",
+        withrefs["refs"][0]["value"] == -14.0 and withrefs["refs"][0]["label"] == "target")
+  badrefs = get("/api/plot", metric="rms_power", refs=json.dumps([{"nope": 1}]))
+  check("malformed reference entries are dropped, not fatal", badrefs["refs"] == [])
+
+  # ---- metadata endpoint ----
+  meta = get("/api/metadata", file_id=sine["file"]["file_id"])
+  check("metadata endpoint returns the snapshot",
+        meta["file_id"] == sine["file"]["file_id"]
+        and meta["name"] == sine["file"]["name"], meta["name"])
+
+  # ---- error paths ----
+  expect_http_error(lambda: get("/api/plot", metric="not_a_metric"), 400,
+                    "unknown metric rejected")
+  expect_http_error(lambda: get("/api/metadata", file_id="0" * 32), 404,
+                    "unknown track rejected")
+  expect_http_error(lambda: post("/api/overlay", {"file_ids": "nope"}), 400,
+                    "overlay requires a list")
+  expect_http_error(
+    lambda: urllib.request.urlopen(urllib.request.Request(
+      f"{BASE}/api/analyse?name=evil.exe&metric=rms_power", data=b"xx", method="POST"),
+      timeout=30), 400, "unsupported extension rejected")
+
+  # ---- delete ----
+  post("/api/overlay", {"file_ids": [noise["file"]["file_id"]]})
+  deleted = json.loads(urllib.request.urlopen(urllib.request.Request(
+    f"{BASE}/api/file?" + urllib.parse.urlencode({"file_id": noise["file"]["file_id"]}),
+    method="DELETE"), timeout=60).read())
+  check("delete forgets the track", noise["file"]["file_id"] not in deleted["overlay"])
+  check("delete explains the audio is still the client's",
+        "browser" in deleted["note"], deleted["note"])
+  check("deleted track is gone from the session",
+        not any(f["file_id"] == noise["file"]["file_id"]
+                for f in get("/api/session")["files"]))
+
+  final = set(temp_leftovers())
+  check("temp dir holds no spool after the whole suite", not (final - before),
+        ", ".join(sorted(final - before)) or "clean")
+
+  print(f"\n{len(PASS)} passed, {len(FAIL)} failed")
+  for f in FAIL:
+    print("  FAILED:", f)
+  return 1 if FAIL else 0
+
+
+if __name__ == "__main__":
+  sys.exit(main())

static/__init__.py

@@ -0,0 +1,11 @@
+"""Packaging shim — not an importable Python module.
+
+`static/` holds the web UI's browser assets (HTML, JS, CSS, vendored uPlot).
+It is declared as a setuptools *package* purely so `[tool.setuptools.package-data]`
+has a package to attach the assets to. Without this file the directory is not a
+package, `package-data` matches nothing, and the built wheel ships without any
+assets at all — leaving an installed `ujm-web` serving 404s for every file.
+
+Nothing imports it. `webapp.py` reads the directory from disk via
+`Path(__file__).parent / "static"`, so the empty module has no runtime role.
+"""

static/app.css

@@ -0,0 +1,270 @@
+/* Audio Mastering Analysis Toolkit — web front end.
+   Dark by default: a spectrogram is read against its surroundings, and the
+   desktop app's pythonic defaults are what these numbers were tuned against. */
+
+:root {
+  --bg: #12141a;
+  --panel: #191c24;
+  --panel-2: #1f232d;
+  --line: #2b303c;
+  --text: #e8eaf0;
+  --muted: #939aa8;
+  --accent: #4fc3f7;
+  --accent-dim: #2b7fa3;
+  --warn: #ffb74d;
+  --error: #ef5350;
+  --ok: #81c784;
+  --radius: 6px;
+  --mono: ui-monospace, "Cascadia Mono", "Source Code Pro", Menlo, Consolas, monospace;
+}
+
+* { box-sizing: border-box; }
+
+html, body {
+  margin: 0;
+  height: 100%;
+  background: var(--bg);
+  color: var(--text);
+  font: 13px/1.45 system-ui, -apple-system, "Segoe UI", Roboto, "Noto Sans", sans-serif;
+  overflow: hidden;
+}
+
+/* ---- top bar ---- */
+
+.topbar {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 16px;
+  height: 48px;
+  padding: 0 14px;
+  background: var(--panel);
+  border-bottom: 1px solid var(--line);
+}
+
+.brand { display: flex; align-items: baseline; gap: 8px; }
+.logo { color: var(--accent); font-size: 16px; }
+.brand-name { font-weight: 600; letter-spacing: .2px; }
+.brand-sub {
+  font-size: 10px;
+  text-transform: uppercase;
+  letter-spacing: 1px;
+  color: var(--bg);
+  background: var(--accent-dim);
+  border-radius: 3px;
+  padding: 1px 5px;
+}
+
+.topbar-controls { display: flex; align-items: center; gap: 8px; flex-wrap: wrap; }
+
+.field { display: flex; align-items: center; gap: 6px; color: var(--muted); font-size: 12px; }
+
+select, .btn, .toggle {
+  background: var(--panel-2);
+  color: var(--text);
+  border: 1px solid var(--line);
+  border-radius: var(--radius);
+  padding: 5px 9px;
+  font: inherit;
+  font-size: 12px;
+  cursor: pointer;
+}
+select:hover, .btn:hover, .toggle:hover { border-color: var(--accent-dim); }
+select:focus-visible, .btn:focus-visible, .toggle:focus-visible { outline: 2px solid var(--accent); outline-offset: 1px; }
+
+.btn.primary { background: var(--accent-dim); border-color: var(--accent); color: #eaf7ff; }
+.btn.primary:hover { background: var(--accent); color: #06202b; }
+.btn.small { padding: 3px 7px; font-size: 11px; }
+.btn:disabled, .toggle:disabled { opacity: .45; cursor: not-allowed; }
+
+.toggle.on { border-color: var(--accent); color: var(--accent); }
+.toggle.off { color: var(--muted); }
+
+.separator { width: 1px; height: 22px; background: var(--line); }
+
+/* ---- layout ---- */
+
+.layout {
+  display: grid;
+  grid-template-columns: 288px minmax(0, 1fr);
+  height: calc(100% - 48px);
+}
+
+.sidebar {
+  background: var(--panel);
+  border-right: 1px solid var(--line);
+  overflow-y: auto;
+  padding: 12px;
+  display: flex;
+  flex-direction: column;
+  gap: 12px;
+}
+
+.panel {
+  background: var(--panel-2);
+  border: 1px solid var(--line);
+  border-radius: var(--radius);
+  padding: 10px;
+}
+.panel h2 {
+  margin: 0 0 8px;
+  font-size: 11px;
+  text-transform: uppercase;
+  letter-spacing: .8px;
+  color: var(--muted);
+  display: flex;
+  align-items: center;
+  gap: 6px;
+}
+.badge {
+  background: var(--line);
+  color: var(--text);
+  border-radius: 8px;
+  padding: 0 6px;
+  font-size: 10px;
+  font-variant-numeric: tabular-nums;
+}
+
+/* ---- file list ---- */
+
+.file-list { list-style: none; margin: 0; padding: 0; display: flex; flex-direction: column; gap: 2px; }
+.file-row {
+  display: flex;
+  align-items: center;
+  gap: 7px;
+  padding: 5px 6px;
+  border-radius: 4px;
+  cursor: pointer;
+  border: 1px solid transparent;
+}
+.file-row:hover { background: #252a35; }
+.file-row.selected { background: #232a38; border-color: var(--accent-dim); }
+.file-row input[type=checkbox] { margin: 0; accent-color: var(--accent-dim); flex: none; }
+.file-swatch { width: 9px; height: 9px; border-radius: 2px; flex: none; }
+.file-name {
+  flex: 1;
+  min-width: 0;
+  white-space: nowrap;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  font-size: 12px;
+}
+.file-remove {
+  flex: none;
+  border: 0;
+  background: none;
+  color: var(--muted);
+  cursor: pointer;
+  font-size: 14px;
+  line-height: 1;
+  padding: 0 2px;
+  opacity: 0;
+}
+.file-row:hover .file-remove { opacity: 1; }
+.file-remove:hover { color: var(--error); }
+
+.empty, .hint { color: var(--muted); font-size: 11.5px; margin: 4px 0 0; }
+.hint code { background: #000; padding: 0 3px; border-radius: 3px; }
+
+/* ---- metadata ---- */
+
+.metadata { display: grid; grid-template-columns: auto 1fr; gap: 3px 10px; margin: 0; font-size: 12px; }
+.metadata dt { color: var(--muted); }
+.metadata dd { margin: 0; text-align: right; font-variant-numeric: tabular-nums; overflow-wrap: anywhere; }
+.metadata dd.muted { color: var(--muted); }
+
+/* ---- reference lines ---- */
+
+.ref-list { list-style: none; margin: 0 0 8px; padding: 0; display: flex; flex-direction: column; gap: 3px; }
+.ref-row { display: flex; align-items: center; gap: 6px; font-size: 12px; }
+.ref-row input[type=color] { width: 20px; height: 18px; padding: 0; border: 1px solid var(--line); background: none; }
+.ref-row input[type=text] { width: 62px; }
+.ref-row input[type=number] { width: 62px; }
+.ref-row input { background: var(--bg); color: var(--text); border: 1px solid var(--line); border-radius: 4px; padding: 2px 4px; font: inherit; font-size: 11px; }
+.ref-row .ref-remove { border: 0; background: none; color: var(--muted); cursor: pointer; }
+.ref-row .ref-remove:hover { color: var(--error); }
+.ref-actions { display: flex; gap: 6px; }
+
+/* ---- plot stage ---- */
+
+.stage { display: flex; flex-direction: column; min-width: 0; padding: 10px 12px 0; }
+
+.plot-head { display: flex; align-items: center; justify-content: space-between; gap: 10px; min-height: 24px; }
+.plot-head h1 { margin: 0; font-size: 13px; font-weight: 600; color: var(--text); }
+.legend { display: flex; flex-wrap: wrap; gap: 10px; font-size: 11.5px; color: var(--muted); }
+.legend .item { display: flex; align-items: center; gap: 5px; }
+.legend .swatch { width: 9px; height: 9px; border-radius: 2px; }
+.legend .annotation { font-family: var(--mono); color: var(--text); }
+
+.plot-host {
+  position: relative;
+  flex: 1;
+  min-height: 200px;
+  margin-top: 6px;
+  background: #0d0f14;
+  border: 1px solid var(--line);
+  border-radius: var(--radius);
+  overflow: hidden;
+}
+.plot-host .uplot { position: absolute; inset: 0; width: 100% !important; height: 100% !important; }
+.plot-host canvas.heatmap { position: absolute; inset: 0; width: 100%; height: 100%; cursor: crosshair; }
+
+.placeholder {
+  position: absolute;
+  inset: 0;
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  justify-content: center;
+  text-align: center;
+  color: var(--muted);
+  gap: 6px;
+  padding: 20px;
+}
+.ph-title { font-size: 15px; color: var(--text); margin: 0; }
+.ph-body { margin: 0; max-width: 44ch; font-size: 12px; }
+.ph-body code { background: #000; padding: 0 3px; border-radius: 3px; }
+
+.statusbar {
+  display: flex;
+  justify-content: space-between;
+  gap: 12px;
+  padding: 6px 2px;
+  font-size: 11.5px;
+  color: var(--muted);
+  min-height: 24px;
+}
+.status.working { color: var(--accent); }
+.status.error { color: var(--error); }
+.status.warn { color: var(--warn); }
+.timing { font-family: var(--mono); }
+
+/* ---- drag & drop ---- */
+
+.drop-overlay {
+  position: fixed;
+  inset: 0;
+  background: rgba(10, 20, 30, .82);
+  border: 3px dashed var(--accent);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  font-size: 20px;
+  color: var(--accent);
+  z-index: 40;
+}
+
+/* ---- tooltip ---- */
+
+.tooltip {
+  position: fixed;
+  background: #05070b;
+  border: 1px solid var(--line);
+  border-radius: 4px;
+  padding: 5px 7px;
+  font: 11px/1.4 var(--mono);
+  color: var(--text);
+  pointer-events: none;
+  z-index: 30;
+  white-space: nowrap;
+}

static/audio-store.js

@@ -0,0 +1,205 @@
+// SPDX-License-Identifier: Apache-2.0
+//
+// Browser-side audio store.
+//
+// Uploaded audio never lives on the server. The File handle from the picker (or
+// drop) is copied into Origin Private File System — a sandboxed, per-origin
+// filesystem the browser owns, which no other site can read and which the OS
+// treats as browser cache, not user data. Everything downstream is driven from
+// there:
+//
+//   * playback reads a blob URL minted from OPFS, so scrubbing a 60 MB WAV
+//     never re-reads the original File
+//   * the SHA-256 that identifies a track is computed over OPFS bytes, so the
+//     id is stable across a reload (the File handle doesn't survive one)
+//   * re-analysis after a page reload re-streams from OPFS instead of asking the
+//     user to pick the file again
+//
+// The server only ever sees the bytes it needs for one request, spooled to a
+// temp file and deleted before the response is written.
+
+const OPFS_DIR = 'ujm-audio';
+
+/** True when the browser can give us a durable private store. */
+export function opfsSupported() {
+  return !!(navigator.storage && navigator.storage.getDirectory);
+}
+
+async function dir() {
+  const root = await navigator.storage.getDirectory();
+  return root.getDirectoryHandle(OPFS_DIR, { create: true });
+}
+
+/** Human-readable reason the store is unusable, or null when it's fine. */
+export async function storageProblem(estimateBytes) {
+  if (!opfsSupported()) return 'this browser has no OPFS support';
+  try {
+    const est = await navigator.storage.estimate();
+    if (est.quota && estimateBytes && estimateBytes > est.quota * 0.9) {
+      return `need ~${mb(estimateBytes)} but only ${mb(est.quota - (est.usage || 0))} of browser storage is free`;
+    }
+    // Ask to be exempt from eviction: without this the browser may clear the
+    // store under pressure, and the file is the only copy we have.
+    if (navigator.storage.persist) await navigator.storage.persist();
+  } catch {
+    // estimate() is optional and can throw in private windows; not fatal.
+  }
+  return null;
+}
+
+function mb(bytes) {
+  return `${(bytes / 1024 / 1024).toFixed(0)} MB`;
+}
+
+/**
+ * Copy a File into OPFS under its content hash.
+ *
+ * Returns {fileId, size}. Uses `createWritable` in a single streamed pass so a
+ * large file is never held in memory in full.
+ */
+export async function put(file, onProgress) {
+  const d = await dir();
+  const tmpName = `.incoming-${Date.now()}-${Math.random().toString(16).slice(2)}`;
+  const handle = await d.getFileHandle(tmpName, { create: true });
+
+  let written = 0;
+  const writable = await handle.createWritable();
+  try {
+    const reader = file.stream().getReader();
+    for (;;) {
+      const {done, value} = await reader.read();
+      if (done) break;
+      await writable.write(value);
+      written += value.byteLength;
+      if (onProgress) onProgress(written, file.size);
+    }
+    await writable.close();
+  } catch (err) {
+    await writable.abort().catch(() => {});
+    await d.removeEntry(tmpName).catch(() => {});
+    throw err;
+  }
+
+  const hash = await sha256(handle);
+  // Content-addressed: the same audio dropped twice costs one copy, and the id
+  // the server keys its analysis on is reproducible.
+  try {
+    await d.removeEntry(hash);
+  } catch {
+    // first time we've seen these bytes
+  }
+  const named = await rename(d, tmpName, hash);
+  const blob = await named.getFile();
+  return {fileId: hash, size: blob.size, sha256: hash};
+}
+
+async function rename(d, from, to) {
+  const fromHandle = await d.getFileHandle(from);
+  const src = await fromHandle.getFile();
+  const toHandle = await d.getFileHandle(to, {create: true});
+  const w = await toHandle.createWritable();
+  await src.stream().pipeTo(w);
+  await d.removeEntry(from);
+  return toHandle;
+}
+
+/** SHA-256 of the stored file, read in chunks so memory stays flat. */
+async function sha256(handle) {
+  const blob = await handle.getFile();
+  const digest = await crypto.subtle.digest('SHA-256', await blob.arrayBuffer());
+  return [...new Uint8Array(digest)]
+    .map((b) => b.toString(16).padStart(2, '0'))
+    .join('')
+    .slice(0, 32);
+}
+
+/** The stored File for an id, or null when it isn't here. */
+export async function get(fileId) {
+  if (!opfsSupported()) return null;
+  try {
+    const d = await dir();
+    const handle = await d.getFileHandle(fileId);
+    return await handle.getFile();
+  } catch {
+    return null;
+  }
+}
+
+export async function has(fileId) {
+  return (await get(fileId)) !== null;
+}
+
+export async function remove(fileId) {
+  if (!opfsSupported()) return;
+  try {
+    const d = await dir();
+    await d.removeEntry(fileId);
+  } catch {
+    // already gone
+  }
+}
+
+/** Ids currently held, newest touched last — used to prune orphans. */
+export async function list() {
+  if (!opfsSupported()) return [];
+  const out = [];
+  const d = await dir();
+  for await (const [name] of d.entries()) {
+    if (!name.startsWith('.incoming-')) out.push(name);
+  }
+  return out;
+}
+
+/** Drop anything `.incoming-*`, i.e. an upload that died mid-write. */
+export async function sweepIncomplete() {
+  if (!opfsSupported()) return 0;
+  const d = await dir();
+  let n = 0;
+  for await (const [name] of d.entries()) {
+    if (name.startsWith('.incoming-')) {
+      await d.removeEntry(name).catch(() => {});
+      n += 1;
+    }
+  }
+  return n;
+}
+
+/**
+ * Stream stored audio to an endpoint as a raw body.
+ *
+ * The body is sent as a stream (duplex: 'half') so a 200 MB file doesn't have to
+ * be materialised as a second in-memory copy just to be uploaded.
+ */
+export async function send(fileId, url, {method = 'POST', onProgress} = {}) {
+  const blob = await get(fileId);
+  if (!blob) throw new Error('audio is no longer in browser storage — re-add the file');
+
+  // Small files go as a plain body: some proxies mishandle streaming duplex
+  // requests, and below a few MB there is nothing to gain.
+  if (blob.size < 8 * 1024 * 1024) {
+    const buf = await blob.arrayBuffer();
+    if (onProgress) onProgress(blob.size, blob.size);
+    return fetch(url, {
+      method,
+      headers: {'Content-Type': 'application/octet-stream'},
+      body: buf,
+    });
+  }
+
+  let sent = 0;
+  const body = blob.stream().pipeThrough(
+    new TransformStream({
+      transform(chunk, controller) {
+        sent += chunk.byteLength;
+        if (onProgress) onProgress(sent, blob.size);
+        controller.enqueue(chunk);
+      },
+    }),
+  );
+  return fetch(url, {
+    method,
+    headers: {'Content-Type': 'application/octet-stream'},
+    body,
+    duplex: 'half',
+  });
+}

static/index.html

@@ -0,0 +1,97 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<title>Audio Mastering Analysis Toolkit</title>
+<link rel="stylesheet" href="/static/vendor/uPlot.min.css">
+<link rel="stylesheet" href="/static/app.css">
+</head>
+<body>
+
+<header class="topbar">
+  <div class="brand">
+    <span class="logo">◉</span>
+    <span class="brand-name">uj-mastering-master</span>
+    <span class="brand-sub">web</span>
+  </div>
+  <div class="topbar-controls">
+    <label class="field">
+      <span>Metric</span>
+      <select id="metric-select" title="Which metric to display"></select>
+    </label>
+    <label class="field">
+      <span>X axis</span>
+      <select id="x-mode-select" title="Absolute time, or each track normalised to its own length">
+        <option value="absolute">Absolute (s)</option>
+        <option value="relative">Relative (%)</option>
+      </select>
+    </label>
+    <button id="toggle-y-log" class="toggle" type="button">Y: log</button>
+    <button id="refresh-plot" class="btn" type="button" title="Redraw from cached data">Refresh</button>
+    <div class="separator"></div>
+    <button id="pick-files" class="btn primary" type="button">Add audio…</button>
+    <input id="file-input" type="file" accept=".mp3,.wav,.flac,.ogg,.oga,.m4a,.aif,.aiff,.opus" multiple hidden>
+  </div>
+</header>
+
+<main class="layout">
+
+  <aside class="sidebar">
+    <section class="panel">
+      <h2>Files <span id="file-count" class="badge">0</span></h2>
+      <ul id="file-list" class="file-list"></ul>
+      <p id="file-empty" class="empty">Drop audio files here, or use <em>Add audio…</em>.
+        Files are held in this browser, not on the server.</p>
+    </section>
+
+    <section class="panel">
+      <h2>Metadata</h2>
+      <dl id="metadata" class="metadata">
+        <dt>Track</dt><dd class="muted">nothing selected</dd>
+      </dl>
+    </section>
+
+    <section class="panel">
+      <h2>Reference lines <span id="ref-count" class="badge">0</span></h2>
+      <ul id="ref-list" class="ref-list"></ul>
+      <div class="ref-actions">
+        <button id="add-ref" class="btn small" type="button">Add at centre</button>
+        <button id="clear-refs" class="btn small" type="button">Clear</button>
+      </div>
+      <p class="hint">Drag a line on the plot to move it. Sets are kept per metric.</p>
+    </section>
+  </aside>
+
+  <section class="stage">
+    <div class="plot-head">
+      <h1 id="plot-title">No track loaded</h1>
+      <div id="legend" class="legend"></div>
+    </div>
+
+    <div id="plot-host" class="plot-host">
+      <div id="placeholder" class="placeholder">
+        <p class="ph-title">Audio Mastering Analysis Toolkit</p>
+        <p class="ph-body">Drop <code>.mp3</code>, <code>.wav</code> or <code>.flac</code> files to analyse.
+          Audio stays in this browser's private storage; the server receives it
+          only for the moment it takes to compute a metric, and writes nothing to
+          disk. Analysis runs at the file's native sample rate.</p>
+      </div>
+      <canvas id="heatmap" class="heatmap" hidden></canvas>
+    </div>
+
+    <div class="statusbar">
+      <span id="status" class="status">Ready</span>
+      <span id="timing" class="timing"></span>
+    </div>
+  </section>
+</main>
+
+<div id="drop-overlay" class="drop-overlay" hidden><span>Drop to analyse</span></div>
+
+<script src="/static/vendor/uPlot.iife.min.js"></script>
+<!-- app.js is an ES module: it imports ./audio-store.js, which owns the
+     browser-side copy of every uploaded file. -->
+<script type="module" src="/static/app.js"></script>
+</body>
+</html>

static/vendor/uPlot.min.css

@@ -0,0 +1 @@
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web_session.py

@@ -0,0 +1,309 @@
+# SPDX-License-Identifier: Apache-2.0
+"""
+Headless analysis service for the web UI.
+
+This is the server-side equivalent of `AnalysisResultsManager` + its worker
+threads: it owns the decode-and-compute lifecycle and the per-file metric cache,
+but it knows nothing about a GUI toolkit. No PyQt import appears in this file or
+anything it imports — that property is what lets `webapp.py` run under a plain
+ASGI server on a box with no display.
+
+## Where the audio lives
+
+The browser is the store of record. The client keeps every uploaded file in OPFS
+(origin-private file system) and re-sends the bytes for each analysis request; the
+server spools them to a temporary file, analyses it, and deletes it in a
+`finally` block. Nothing this module or the API layer does leaves an audio file
+behind on the host.
+
+That is a deliberate trade, made because the analysis backend is
+`master_core.AudioFile` -> `librosa.load(path)` -> numpy/scipy. Decoding needs a
+real path, and the metrics need the samples in *this* process, so the bytes must
+transit the host. What the design guarantees is that they never *persist* there:
+no upload directory, no files surviving a request, and no server state keyed on a
+path the client chose. A crash mid-analysis can leave a file in `tempfile`'s
+directory, which is the OS's to clean; there is no application-owned location
+that accumulates audio.
+
+The cost is bandwidth: switching metrics re-uploads the track. For a local
+workstation deployment that is a loopback copy of a few tens of megabytes, which
+is cheaper than the alternative (an LRU cache of decoded signals) — and the
+client only re-sends when the metric isn't already computed, because the computed
+*data* is cached here, keyed by content hash.
+
+## Content addressing
+
+`file_id` is the SHA-256 of the audio bytes, computed by the client. Using the
+hash rather than the filename means:
+
+- two takes with the same name never collide, and renaming a file doesn't orphan
+  its cached metrics;
+- the server can key its cache on the bytes actually analysed, so a client that
+  re-sends the same file gets the cached result without re-decoding;
+- nothing the client sends is used to construct a path, so there is no traversal
+  surface to defend.
+
+## Differences from the desktop manager, and why
+
+- **No prefetch.** The desktop app warms every metric for the loaded file so a
+  dropdown switch is instant. Analysing in a browser is request-driven, and
+  prefetching seven metrics on every upload would occupy a core for minutes on a
+  long track while the user looks at one plot. So `compute()` runs on demand and
+  the result is cached.
+- **One lock, not a thread-per-job.** Long analysis holds the CPU — numpy and
+  scipy release the GIL, but concurrent librosa loads on the same box just thrash
+  the cache and make every request slower. Serialising here also keeps the
+  `metric_data` cache simple to reason about.
+- **The decoded signal is not kept.** Once a metric is computed, the `AudioFile`
+  is dropped: the samples are the expensive part (tens of MB of float32 for a
+  4-minute track), and every metric we ship is computed from one pass. Holding
+  them to save a decode on a *second* metric costs more memory than the re-upload
+  costs time.
+
+`AudioFile` itself memoises the K-weighted signal so the three metrics that share
+it (LUFS and PSR via `_short_term_lufs`, Crest Factor's windowing) don't each
+re-filter the audio within a single request.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import logging
+import threading
+import time
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any, Optional
+
+from master_core import AudioFile
+from metrics import METRICS, DEFAULT_METRIC_ID
+
+logger = logging.getLogger(__name__)
+
+# Suffixes the decoder is expected to handle. The client filters on these too,
+# but the server is the authority — a client is not a trusted input.
+AUDIO_SUFFIXES = frozenset({
+  ".wav", ".mp3", ".flac", ".ogg", ".oga", ".opus", ".m4a", ".aac",
+  ".aiff", ".aif", ".aifc", ".wma", ".mp4", ".webm",
+})
+
+# Spool chunk while receiving the body: 1 MiB keeps peak memory flat regardless
+# of file size while not hammering the syscall boundary.
+_SPOOL_CHUNK = 1024 * 1024
+
+
+@dataclass(frozen=True)
+class AudioFileSnapshot:
+  """The bits of an `AudioFile` the API needs, without the decoded signal."""
+  file_id: str
+  name: str
+  song_name: str
+  sample_rate: int
+  duration: float
+  max_amplitude: float
+  avg_amplitude: float
+  size_bytes: int = 0
+
+  @property
+  def channels(self) -> int:
+    """Always 1: analysis is mono.
+
+    `librosa.load` downmixes to mono by default and `AudioFile` stores the mono
+    signal, so every metric here measures the mono sum — same as the desktop app.
+    The field is kept explicit (rather than omitted) because a "0.0 dBTP on a
+    stereo master" reading is only meaningful once you know that.
+    """
+    return 1
+
+  def as_dict(self) -> dict[str, Any]:
+    return {
+      "file_id": self.file_id,
+      "name": self.name,
+      "song_name": self.song_name,
+      "sample_rate": self.sample_rate,
+      "duration": self.duration,
+      "max_amplitude": self.max_amplitude,
+      "avg_amplitude": self.avg_amplitude,
+      "channels": self.channels,
+      "size_bytes": self.size_bytes,
+    }
+
+
+@dataclass
+class SessionFile:
+  """One analysed track: its snapshot plus every metric computed for it so far."""
+  snapshot: AudioFileSnapshot
+  metric_data: dict[str, Any] = field(default_factory=dict)
+
+  def metadata(self) -> dict[str, Any]:
+    payload = self.snapshot.as_dict()
+    payload["metrics_cached"] = sorted(self.metric_data.keys())
+    return payload
+
+
+def file_id_for(data: bytes) -> str:
+  """Content hash used as the session key (see the module docstring)."""
+  return hashlib.sha256(data).hexdigest()[:32]
+
+
+# Spool chunk while receiving a body: 1 MiB keeps peak memory flat regardless of
+# file size while not hammering the syscall boundary.
+SPOOL_CHUNK = 1024 * 1024
+
+
+class AnalysisSession:
+  """Server-side state: analysed tracks keyed by content hash, and the view set."""
+
+  def __init__(self, max_files: int = 64) -> None:
+    self.files: dict[str, SessionFile] = {}
+    # File ids currently drawn (the desktop app's file-list checkboxes).
+    self.overlay: list[str] = []
+    self.max_files = max_files
+    self._lock = threading.RLock()
+
+  # ---- loading ------------------------------------------------------------
+
+  def load(self, path: Path, file_id: str, name: str, size_bytes: int = 0) -> SessionFile:
+    """Decode `path` (a spool that the caller owns) into the session.
+
+    Idempotent by `file_id`: a client re-sending the same bytes for a metric that
+    isn't cached yet re-uses the existing snapshot rather than re-decoding.
+    """
+    with self._lock:
+      existing = self.files.get(file_id)
+      if existing is not None:
+        return existing
+
+    t0 = time.perf_counter()
+    audio = AudioFile(str(path))
+    snapshot = AudioFileSnapshot(
+      file_id=file_id,
+      name=name,
+      song_name=audio.song_name,
+      sample_rate=int(audio.sr),
+      duration=float(len(audio.y_mono) / audio.sr) if audio.sr else 0.0,
+      max_amplitude=float(audio.max_amplitude),
+      avg_amplitude=float(audio.avg_amplitude),
+      size_bytes=size_bytes,
+    )
+    entry = SessionFile(snapshot=snapshot)
+    logger.info(
+      "Loaded %s in %.1fs (%.0f s @ %d Hz, %s)",
+      snapshot.song_name, time.perf_counter() - t0,
+      snapshot.duration, snapshot.sample_rate, file_id[:8],
+    )
+    with self._lock:
+      self.files[file_id] = entry
+      self._evict_locked()
+      if file_id not in self.overlay:
+        self.overlay.append(file_id)
+      return entry
+
+  # ---- metrics ------------------------------------------------------------
+
+  def compute_metric(self, path: Path, file_id: str, metric_id: str,
+                     name: str = "upload", size_bytes: int = 0) -> Any:
+    """Metric data for a track, computed (and cached) if needed.
+
+    `path` is a spool the caller owns and will delete; this method only reads it.
+    """
+    metric = METRICS.get(metric_id)
+    if metric is None:
+      raise KeyError(f"Unknown metric: {metric_id}")
+
+    with self._lock:
+      entry = self.files.get(file_id)
+      if entry is not None:
+        cached = entry.metric_data.get(metric_id)
+        if cached is not None:
+          return cached
+
+    t0 = time.perf_counter()
+    audio = AudioFile(str(path))
+    if entry is None:
+      # First contact with these bytes: snapshot it while we have them decoded.
+      entry = self.load(path, file_id, name, size_bytes)
+    data = metric.compute(audio)
+    elapsed = time.perf_counter() - t0
+    logger.info("%s on %s in %.2fs", metric.display_name,
+                entry.snapshot.song_name, elapsed)
+
+    with self._lock:
+      # Keep the first result if a concurrent request won the race — identical,
+      # because both hashed the same bytes.
+      entry.metric_data.setdefault(metric_id, data)
+      return entry.metric_data[metric_id]
+
+  def observe(self, path: Path, file_id: str, name: str, size_bytes: int = 0) -> SessionFile:
+    """Decode just enough to register a track (used for metadata-only requests)."""
+    return self.load(path, file_id, name, size_bytes)
+
+  # ---- lifecycle ----------------------------------------------------------
+
+  def drop(self, file_id: str) -> bool:
+    """Forget a track and everything computed for it.
+
+    Nothing to delete on disk: the audio was never persisted. The browser still
+    holds its copy, which is why this is the client's decision to make.
+    """
+    with self._lock:
+      entry = self.files.pop(file_id, None)
+      if file_id in self.overlay:
+        self.overlay.remove(file_id)
+    return entry is not None
+
+  def clear(self) -> None:
+    with self._lock:
+      self.files.clear()
+      self.overlay.clear()
+
+  def _evict_locked(self) -> None:
+    """Bound the cache so a long-lived server can't grow without limit.
+
+    Evicts whole tracks, oldest first. The client can always re-upload, so the
+    worst case is a re-decode rather than an error.
+    """
+    while len(self.files) > self.max_files:
+      oldest = next(iter(self.files))
+      self.files.pop(oldest, None)
+      if oldest in self.overlay:
+        self.overlay.remove(oldest)
+      logger.info("Evicted %s from the analysis cache", oldest[:8])
+
+  # ---- view set -----------------------------------------------------------
+
+  def set_overlay(self, file_ids: list[str]) -> list[str]:
+    """Replace the drawn set, keeping only ids this session has analysed."""
+    with self._lock:
+      self.overlay = [f for f in file_ids if f in self.files]
+      return list(self.overlay)
+
+  def toggle(self, file_id: str, checked: bool) -> list[str]:
+    with self._lock:
+      if file_id not in self.files:
+        return list(self.overlay)
+      if checked and file_id not in self.overlay:
+        self.overlay.append(file_id)
+      elif not checked and file_id in self.overlay:
+        self.overlay.remove(file_id)
+      return list(self.overlay)
+
+  def overlay_entries(self) -> list[SessionFile]:
+    with self._lock:
+      return [self.files[f] for f in self.overlay if f in self.files]
+
+  def entry(self, file_id: str) -> Optional[SessionFile]:
+    with self._lock:
+      return self.files.get(file_id)
+
+  def snapshot_size(self) -> int:
+    """Number of tracks held in the analysis cache — surfaced in /api/session."""
+    with self._lock:
+      return len(self.files)
+
+
+# One process-wide session. The server is single-user by design (it runs on a
+# workstation and analyses files the user picked), so per-connection sessions
+# would only duplicate an expensive decode of the same audio.
+SESSION = AnalysisSession()
+DEFAULT_METRIC = DEFAULT_METRIC_ID

webapp.py

@@ -0,0 +1,451 @@
+# SPDX-License-Identifier: Apache-2.0
+"""
+Web front end for the mastering toolkit.
+
+Same backend as the desktop app — `master_core.AudioFile` for decode,
+`metrics.METRICS[...].compute` for the numbers — with the PyQt5 layer replaced by
+a JSON API and a browser canvas. `metrics.Metric` was already split into a
+backend-neutral `compute` and a view-aware `build_spec`, so this costs no changes
+to the analysis code; `metrics_json` is the new renderer seam.
+
+Run it:
+
+    uv run ujm-web                       # http://127.0.0.1:8000
+    uv run ujm-web --host 0.0.0.0 --port 8080 --open
+
+Design notes:
+
+- **The browser holds the audio; the server holds only computed data.** The
+  client keeps every uploaded track in OPFS and PUTs the bytes for each analysis
+  request. The server spools the body to a temp file, decodes, computes, and
+  deletes it inside a `finally` — there is no upload directory and no audio file
+  survives a request. `web_session`'s docstring explains why the bytes still have
+  to reach this process (librosa decodes by path) and what that does and doesn't
+  guarantee. Concretely: hosting this does not accumulate the user's masters on
+  the host.
+- **Nothing is keyed on a client-supplied path.** `file_id` is the SHA-256 of the
+  audio bytes, so there is no traversal surface and no filename collision; the
+  only place a client string reaches the spool is its extension, which is matched
+  against an allow-list.
+- **Analysis runs in the event loop's threadpool, not in the loop.** Metric
+  computes are CPU-bound numpy/scipy calls that do release the GIL; a plain `def`
+  endpoint is dispatched to Starlette's threadpool, so a long spectrogram doesn't
+  block status requests.
+- **Bodies are read as a stream.** `await request.stream()` is written straight to
+  the spool, so a 200 MB master never sits in RAM as one `bytes` object.
+- **Nothing is served by a CDN.** The front end (uPlot for curves, a plain canvas
+  for the spectrogram) is vendored under `static/` and the server binds loopback
+  by default: mastering work-in-progress shouldn't leak out of the box.
+- **`/api/plot` is a pure view render.** Lin/log, time mode and the reference-line
+  set are query parameters, so a view change costs a JSON re-serialisation from
+  the cache — never a recompute. That is the property that made the desktop app
+  feel fast; the web UI keeps it.
+"""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import logging
+import tempfile
+from pathlib import Path
+from typing import Any, Optional
+
+from fastapi import Body, FastAPI, HTTPException, Query, Request
+from fastapi.concurrency import run_in_threadpool
+from fastapi.responses import FileResponse, JSONResponse
+from fastapi.staticfiles import StaticFiles
+
+from logger_setup import setup_logging
+from metrics import METRICS, DEFAULT_METRIC_ID
+from metrics_json import serialize_ref_lines, serialize_spec, serialize_view
+from plotspec import RefLineProps, ViewState, X_ABSOLUTE, X_RELATIVE, apply_x_mode
+from web_session import AUDIO_SUFFIXES, SESSION, DEFAULT_METRIC, file_id_for
+
+STATIC_DIR = Path(__file__).parent / "static"
+
+logger = logging.getLogger(__name__)
+
+app = FastAPI(
+  title="uj-mastering-master (web)",
+  description="Audio mastering analysis metrics over HTTP.",
+  version="0.1.0",
+)
+
+
+# ---- request helpers -------------------------------------------------------
+
+def _query(request: Request, key: str) -> Optional[str]:
+  """Read a query parameter.
+
+  FastAPI's `Query` only populates declared signature parameters, and these
+  endpoints take a raw body rather than a parameter list, so the two values the
+  client sends alongside the audio are pulled off the URL directly.
+  """
+  value = request.query_params.get(key)
+  return value or None
+
+
+def _suffix_or_400(name: str) -> str:
+  suffix = Path(name or "").suffix.lower()
+  if suffix not in AUDIO_SUFFIXES:
+    raise HTTPException(
+      status_code=400,
+      detail=f"Unsupported format '{suffix or '?'}' "
+             f"(expected one of {', '.join(sorted(AUDIO_SUFFIXES))})",
+    )
+  return suffix
+
+
+def _require_file(file_id: str):
+  entry = SESSION.entry(file_id)
+  if entry is None:
+    raise HTTPException(status_code=404, detail="Track not analysed in this session")
+  return entry
+
+
+def _metric_or_400(metric: Optional[str]) -> str:
+  uid = metric or DEFAULT_METRIC_ID
+  if uid not in METRICS:
+    raise HTTPException(status_code=400, detail=f"Unknown metric: {uid}")
+  return uid
+
+
+# ---- catalogue & session ---------------------------------------------------
+
+def _metric_catalogue() -> list[dict]:
+  return [
+    {
+      "id": m.id,
+      "display_name": m.display_name,
+      "default": m.id == DEFAULT_METRIC_ID,
+    }
+    for m in METRICS.values()
+  ]
+
+
+@app.get("/api/metrics")
+def list_metrics():
+  return {"metrics": _metric_catalogue(), "default": DEFAULT_METRIC_ID}
+
+
+@app.get("/api/session")
+def session_state():
+  return {
+    "files": [f.metadata() for f in SESSION.files.values()],
+    "overlay": list(SESSION.overlay),
+    "default_metric": DEFAULT_METRIC_ID,
+    # Explicit, so the front end can state it in the UI and a reader of the API
+    # can confirm there is no audio store behind this server.
+    "audio_storage": "client (browser OPFS) — nothing persisted server-side",
+  }
+
+
+# ---- analysis --------------------------------------------------------------
+
+@app.post("/api/analyse")
+async def analyse(
+  request: Request,
+  file_id: Optional[str] = Query(None, description="SHA-256 of the body; computed if absent"),
+  name: str = Query("upload", description="Original filename, for display only"),
+  metric: Optional[str] = Query(None),
+):
+  """Decode and measure one track, sent as a raw body.
+
+  Returns the snapshot plus the serialised metric payload in a single round trip:
+  the client has to send the bytes either way, so making it then ask again for the
+  plot would upload the same file twice.
+
+  Declared `async` so the body can be streamed to the spool with `await`; the
+  decode/compute that follows is a blocking call, so it is handed to the
+  threadpool explicitly to keep the event loop free.
+  """
+  uid = _metric_or_400(metric)
+  suffix = _suffix_or_400(name)
+  display_name = Path(name).name
+
+  spool = tempfile.NamedTemporaryFile(prefix="ujm-", suffix=suffix, delete=False)
+  path = Path(spool.name)
+  try:
+    size = 0
+    with spool:
+      async for chunk in request.stream():
+        spool.write(chunk)
+        size += len(chunk)
+    if size == 0:
+      raise HTTPException(status_code=400, detail="Empty request body")
+
+    fid = file_id or await run_in_threadpool(_hash_file, path)
+
+    def _work() -> tuple[Any, Any]:
+      entry = SESSION.load(path, fid, display_name, size)
+      data = SESSION.compute_metric(path, fid, uid, display_name, size)
+      spec = METRICS[uid].build_spec(data, ViewState())
+      return entry, spec
+
+    entry, spec = await run_in_threadpool(_work)
+  finally:
+    # The guarantee this design makes: no audio outlives the request.
+    path.unlink(missing_ok=True)
+
+  payload = serialize_spec(spec)
+  return {
+    "file": entry.metadata(),
+    "metric": uid,
+    "metric_name": METRICS[uid].display_name,
+    "payload": payload,
+    "axes": payload["axes"],
+    "overlay": list(SESSION.overlay),
+  }
+
+
+def _hash_file(path: Path) -> str:
+  """SHA-256 of a spooled body, read in chunks."""
+  digest = hashlib.sha256()
+  with path.open("rb") as handle:
+    for block in iter(lambda: handle.read(1024 * 1024), b""):
+      digest.update(block)
+  return digest.hexdigest()[:32]
+
+
+# ---- plotting --------------------------------------------------------------
+
+@app.get("/api/metadata")
+def metadata(file_id: str):
+  return _require_file(file_id).metadata()
+
+
+@app.post("/api/file")
+async def analyse_extra(request: Request, file_id: Optional[str] = Query(None),
+                        name: str = Query("upload")):
+  """Register a track without plotting it.
+
+  Used when the client wants the file on the list (duration, amplitudes, tags)
+  for a metric that is already drawn, so the plot endpoint doesn't need to
+  re-upload it.
+  """
+  suffix = _suffix_or_400(name)
+  display_name = Path(name).name
+
+  spool = tempfile.NamedTemporaryFile(prefix="ujm-", suffix=suffix, delete=False)
+  path = Path(spool.name)
+  try:
+    size = 0
+    with spool:
+      async for chunk in request.stream():
+        spool.write(chunk)
+        size += len(chunk)
+    if size == 0:
+      raise HTTPException(status_code=400, detail="Empty request body")
+
+    fid = file_id or await run_in_threadpool(_hash_file, path)
+    entry = await run_in_threadpool(SESSION.observe, path, fid, display_name, size)
+  finally:
+    path.unlink(missing_ok=True)
+
+  return {"file": entry.metadata(), "overlay": list(SESSION.overlay)}
+
+
+@app.post("/api/overlay")
+def set_overlay(payload: dict = Body(...)):
+  ids = payload.get("file_ids")
+  if not isinstance(ids, list):
+    raise HTTPException(status_code=400, detail="'file_ids' must be a list")
+  return {"overlay": SESSION.set_overlay([str(i) for i in ids])}
+
+
+@app.delete("/api/file")
+def delete_file(file_id: str):
+  if not SESSION.drop(file_id):
+    raise HTTPException(status_code=404, detail="Track not analysed in this session")
+  return {"overlay": list(SESSION.overlay),
+          "note": "server forgot the analysis; the browser still holds the audio"}
+
+
+@app.get("/api/plot")
+def plot(
+  metric: str = Query(DEFAULT_METRIC),
+  y_log: Optional[bool] = Query(None),
+  x_log: Optional[bool] = Query(None),
+  x_mode: str = Query(X_ABSOLUTE),
+  refs: str = Query("", description="JSON list of reference lines"),
+):
+  """Draw the current overlay of `metric`, honouring view state.
+
+  Pure view render: every dataset here was already computed by `/api/analyse`, so
+  a lin/log flip or a time-mode change never touches numpy. Returns one
+  serialised dataset per drawn file plus the shared axis description, mirroring
+  the desktop `show_specs([(label, PlotSpec, colour), ...])`.
+  """
+  if metric not in METRICS:
+    raise HTTPException(status_code=400, detail=f"Unknown metric: {metric}")
+  if x_mode not in (X_ABSOLUTE, X_RELATIVE):
+    raise HTTPException(status_code=400, detail=f"Unknown x_mode: {x_mode}")
+
+  view = ViewState(y_log=y_log, x_log=x_log, x_mode=x_mode)
+  ref_lines = _parse_refs(refs)
+
+  entries = SESSION.overlay_entries()
+  if not entries:
+    return {
+      "metric": metric, "metric_name": METRICS[metric].display_name,
+      "view": serialize_view(view), "refs": serialize_ref_lines(ref_lines),
+      "datasets": [], "axes": None, "warnings": [],
+    }
+
+  datasets, warnings = [], []
+  for index, entry in enumerate(entries):
+    data = entry.metric_data.get(metric)
+    if data is None:
+      # Never analysed this metric for this track: the client has the bytes and
+      # knows to send them. Say so rather than recomputing from nothing.
+      warnings.append(f"{entry.snapshot.song_name}: {METRICS[metric].display_name} "
+                      f"not computed yet")
+      continue
+    try:
+      spec = METRICS[metric].build_spec(data, view)
+    except Exception as exc:
+      logger.exception("build_spec failed for %s", metric)
+      warnings.append(f"{entry.snapshot.song_name}: {exc}")
+      continue
+
+    if view.x_mode == X_RELATIVE:
+      spec = apply_x_mode(spec, view.x_mode)
+
+    datasets.append({
+      "file_id": entry.snapshot.file_id,
+      "label": entry.snapshot.song_name,
+      "index": index,
+      "payload": serialize_spec(spec),
+      # The client assigns colours; it keeps a song's colour stable across
+      # metric switches the same way the desktop palette-by-row does.
+      "palette_index": _palette_index(entry.snapshot.file_id),
+    })
+
+  # Heatmaps don't overlay: only the first drawn dataset is rendered, as on the
+  # desktop, so the browser isn't sent z-grids it will throw away.
+  if datasets and datasets[0]["payload"]["heatmap"] is not None and len(datasets) > 1:
+    warnings.append(
+      f"{METRICS[metric].display_name}: one track at a time — "
+      f"showing {datasets[0]['label']}"
+    )
+    datasets = datasets[:1]
+
+  return {
+    "metric": metric,
+    "metric_name": METRICS[metric].display_name,
+    "view": serialize_view(view),
+    "refs": serialize_ref_lines(ref_lines),
+    "datasets": datasets,
+    "axes": datasets[0]["payload"]["axes"] if datasets else None,
+    "warnings": warnings,
+    "recompute_free": True,
+  }
+
+
+def _palette_index(file_id: str) -> int:
+  """Stable palette slot for a track, by first-seen order in the session."""
+  order = list(SESSION.files.keys())
+  try:
+    return order.index(file_id)
+  except ValueError:
+    return 0
+
+
+def _parse_refs(raw: str) -> list[RefLineProps]:
+  if not raw:
+    return []
+  try:
+    items = json.loads(raw)
+  except ValueError:
+    raise HTTPException(status_code=400, detail="refs must be JSON")
+  if not isinstance(items, list):
+    raise HTTPException(status_code=400, detail="refs must be a JSON list")
+  lines = []
+  for item in items:
+    if not isinstance(item, dict) or "value" not in item:
+      continue
+    try:
+      value = float(item["value"])
+    except (TypeError, ValueError):
+      continue
+    lines.append(RefLineProps(
+      value=value,
+      color=str(item.get("color", "#444444")),
+      style=str(item.get("style", "dash")),
+      label=str(item.get("label", "")),
+    ))
+  return lines
+
+
+# ---- front end -------------------------------------------------------------
+
+@app.get("/")
+def index():
+  index_file = STATIC_DIR / "index.html"
+  if not index_file.exists():
+    raise HTTPException(status_code=500, detail="Front end assets missing")
+  return FileResponse(index_file)
+
+
+if STATIC_DIR.exists():
+  app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
+
+
+@app.exception_handler(Exception)
+async def unhandled(request, exc):  # pragma: no cover - safety net
+  logger.exception("Unhandled error on %s", request.url.path)
+  return JSONResponse(status_code=500, content={"detail": str(exc)})
+
+
+# ---- entry point -----------------------------------------------------------
+
+# Our CLI speaks `logger_setup`'s vocabulary (ERROR/WARN/INFO/DEBUG/TRACE);
+# uvicorn only accepts its own names. Translate rather than passing through —
+# `--log-level WARN` used to die with KeyError: 'warn'.
+_UVICORN_LEVEL = {
+  "ERROR": "error",
+  "WARN": "warning",
+  "INFO": "info",
+  "DEBUG": "debug",
+  "TRACE": "debug",
+}
+
+
+def main() -> None:
+  import uvicorn
+
+  parser = argparse.ArgumentParser(
+    prog="ujm-web",
+    description="Mastering analysis toolkit — web front end",
+  )
+  parser.add_argument("--host", default="127.0.0.1",
+                      help="interface to bind (default: %(default)s — loopback)")
+  parser.add_argument("--port", type=int, default=8000)
+  parser.add_argument("--open", action="store_true",
+                      help="open the UI in a browser on startup")
+  parser.add_argument("--reload", action="store_true", help="auto-reload on edits")
+  parser.add_argument("--log-level", "-l", default="INFO",
+                      choices=["ERROR", "WARN", "INFO", "DEBUG", "TRACE"])
+  parser.add_argument("--log-file", action="store_true",
+                      help="also write audio_analysis.log")
+  args = parser.parse_args()
+
+  setup_logging(level=args.log_level, log_to_file=args.log_file)
+  url = f"http://{args.host if args.host != '0.0.0.0' else '127.0.0.1'}:{args.port}"
+  logger.info("Web UI at %s", url)
+  logger.info("Audio is stored in the browser (OPFS); "
+              "uploads are spooled to temp and deleted after each request")
+
+  if args.open:
+    import threading
+    import webbrowser
+    threading.Timer(1.0, lambda: webbrowser.open(url)).start()
+
+  uvicorn.run("webapp:app", host=args.host, port=args.port, reload=args.reload,
+              log_level=_UVICORN_LEVEL[args.log_level])
+
+
+if __name__ == "__main__":
+  main()