feat(onboarding): guided first-run tour with background FFmpeg provisioning

Phase 5 of the 0.1.0 release prep: - FFmpeg no longer blocks startup (or crashes the app offline): provisioning runs in a background thread emitting throttled ffmpeg-progress events, with installed/downloading/failed state queryable via get_ffmpeg_status and a retry command - video jobs are invisible to claiming and tier-priority checks until FFmpeg is ready, so they wait as pending without failing — and without starving image embeddings/tagging (include_videos gating in db.rs) - 7-step show-don't-tell onboarding wizard: welcome + live FFmpeg progress, real first-folder picker, faked animating pipeline bar, placeholder gallery tiles, cycling search-syntax demo, views overview, and an AI features step with a real opt-in tagger download - skippable at every point (Escape included), persisted via settings/onboarding_completed.txt, re-runnable from Settings > General, which also gains an FFmpeg status/retry row
2026-06-12 23:09:05 +01:00
parent 1640e30330
commit 7403f0cfeb
17 changed files with 1139 additions and 30 deletions
@@ -0,0 +1,96 @@
+import { useEffect } from "react";
+import { useGalleryStore } from "../../store";
+import { FakeProgressBar } from "./fakes";
+
+const FAKE_TAGS = ["landscape", "sunset", "outdoors", "no_humans", "ocean", "cloudy_sky"];
+
+export function StepAiFeatures() {
+  const taggerModelStatus = useGalleryStore((s) => s.taggerModelStatus);
+  const taggerModelPreparing = useGalleryStore((s) => s.taggerModelPreparing);
+  const taggerModelProgress = useGalleryStore((s) => s.taggerModelProgress);
+  const prepareTaggerModel = useGalleryStore((s) => s.prepareTaggerModel);
+  const loadTaggerModelStatus = useGalleryStore((s) => s.loadTaggerModelStatus);
+
+  useEffect(() => {
+    void loadTaggerModelStatus();
+  }, [loadTaggerModelStatus]);
+
+  const taggerReady = taggerModelStatus?.ready ?? false;
+
+  return (
+    <div>
+      <p className="text-sm leading-relaxed text-gray-300">
+        Two optional AI features run entirely on this machine — nothing is sent anywhere. Both are
+        one-time downloads you can also start later from Settings.
+      </p>
+
+      <h4 className="mt-6 text-[12px] font-semibold uppercase tracking-[0.08em] text-gray-400">AI tagging</h4>
+      <div className="mt-1 divide-y divide-white/[0.05]">
+        <div className="py-4">
+          <div className="flex items-start justify-between gap-6">
+            <div className="min-w-0">
+              <p className="text-sm text-white">Automatic tags for every image</p>
+              <p className="mt-1 text-xs leading-relaxed text-gray-500">
+                The WD tagger model (~1.3 GB download) labels images so you can search with{" "}
+                <code className="rounded bg-white/[0.07] px-1 py-0.5 text-[11px] text-gray-200">/t</code> — tags look like:
+              </p>
+              <span className="mt-2 flex flex-wrap gap-1.5">
+                {FAKE_TAGS.map((tag) => (
+                  <span key={tag} className="rounded-md border border-white/10 bg-white/[0.04] px-2 py-0.5 text-[11px] text-gray-400">
+                    {tag}
+                  </span>
+                ))}
+              </span>
+            </div>
+            <div className="shrink-0">
+              {taggerReady ? (
+                <span className="inline-flex rounded-md border border-emerald-400/25 bg-emerald-500/10 px-2 py-0.5 text-[11px] font-medium text-emerald-300">
+                  Installed
+                </span>
+              ) : (
+                <button
+                  className="rounded-md border border-white/10 bg-white/[0.055] px-3 py-1.5 text-xs text-gray-300 transition-colors hover:bg-white/10 hover:text-white disabled:cursor-not-allowed disabled:opacity-45"
+                  onClick={() => void prepareTaggerModel()}
+                  disabled={taggerModelPreparing}
+                >
+                  {taggerModelPreparing ? "Downloading..." : "Download now"}
+                </button>
+              )}
+            </div>
+          </div>
+          {taggerModelPreparing ? (
+            <div className="mt-3">
+              <FakeProgressBar
+                fraction={
+                  taggerModelProgress && taggerModelProgress.total_files > 0
+                    ? taggerModelProgress.completed_files / taggerModelProgress.total_files
+                    : null
+                }
+              />
+              {taggerModelProgress?.current_file ? (
+                <p className="mt-1.5 truncate text-[11px] text-gray-600">{taggerModelProgress.current_file}</p>
+              ) : null}
+            </div>
+          ) : null}
+        </div>
+      </div>
+
+      <h4 className="mt-6 text-[12px] font-semibold uppercase tracking-[0.08em] text-gray-400">Semantic search & similarity</h4>
+      <div className="mt-1 divide-y divide-white/[0.05]">
+        <div className="py-4">
+          <p className="text-sm text-white">Search by meaning, find look-alikes</p>
+          <p className="mt-1 text-xs leading-relaxed text-gray-500">
+            Powers <code className="rounded bg-white/[0.07] px-1 py-0.5 text-[11px] text-gray-200">/s</code> search and
+            "find similar". The CLIP model (~330 MB) downloads automatically the first time embeddings are
+            generated — no action needed; you'll see it in the background-tasks bar.
+          </p>
+        </div>
+      </div>
+
+      <p className="mt-5 text-xs leading-relaxed text-gray-500">
+        That's the tour. Add folders from the sidebar, and revisit any of this from Settings — including
+        re-running this tour.
+      </p>
+    </div>
+  );
+}