Memby v0.1.53: Android TV client plus gateway
Android TV client for Emby (Kotlin, Compose for TV) and the Memby gateway (Go, Postgres, Redis) that fronts it. Client: - Setup, profiles, home rows, Media3 playback, system screensaver (Dream) - Backend chosen at build time: gateway when memby.gatewayUrl is set, otherwise direct to Emby. Both paths stay working. - Server-composed home rows, rendered verbatim so new row types ship without an app release - Full-screen animated maintenance state, row engagement telemetry Gateway: - One request per TV screen; auth, caching, search and row shaping - Library import from Emby into Postgres (manual, then hourly incremental) - Recommendations from viewing history (recency-weighted genre affinity) - Admin page for imports, an offline switch, and per-row analytics - Video always direct-plays from Emby; only metadata passes through Identity is com.ponzischeme89.memby throughout, replacing com.mattcohen.embyclientsname. A changed applicationId installs as a new app: TVs need a fresh sign-in and the old package uninstalled. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
ponzischeme89
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package recommend
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import (
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"context"
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"encoding/json"
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"log/slog"
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"net/url"
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"strconv"
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"strings"
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"sync"
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"github.com/ponzischeme89/memby/server/internal/emby"
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)
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// Row is one horizontal strip on the TV home screen.
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type Row struct {
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ID string `json:"id"`
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Title string `json:"title"`
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Kind string `json:"kind"`
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Items []json.RawMessage `json:"items"`
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}
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// Source is the slice of the Emby client this package needs, narrowed so tests can
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// supply a fake without a server.
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type Source interface {
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Items(ctx context.Context, cred emby.Credentials, params url.Values) (*emby.ItemsResult, error)
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Similar(ctx context.Context, cred emby.Credentials, itemID string, params url.Values) (*emby.ItemsResult, error)
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}
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// LibrarySource is the imported catalogue. When present, the candidate pool comes from
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// Postgres instead of Emby, which takes the rebuild off Emby entirely.
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type LibrarySource interface {
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LibraryCandidates(ctx context.Context, genres []string, limit int) ([]json.RawMessage, error)
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}
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type Engine struct {
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source Source
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log *slog.Logger
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// Library is optional; nil (or an empty library) falls back to querying Emby.
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Library LibrarySource
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// MinRowItems is the shortest row worth showing. A two-item "Recommended" strip
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// looks broken next to full rows, so short rows are dropped entirely.
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MinRowItems int
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// MaxSimilarRows caps "Because you watched …" rows so the home screen stays a home
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// screen rather than a wall of near-duplicates.
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MaxSimilarRows int
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RowSize int
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}
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func NewEngine(source Source, log *slog.Logger) *Engine {
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return &Engine{
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source: source,
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log: log,
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MinRowItems: 4,
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MaxSimilarRows: 2,
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RowSize: 20,
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}
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}
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const (
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historyFields = "Genres,Studios,CommunityRating,SeriesName,ProductionYear,RunTimeTicks"
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candidateFields = "Genres,Studios,CommunityRating,ProductionYear,RunTimeTicks,PrimaryImageAspectRatio"
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rowImageTypes = "Backdrop,Primary,Logo"
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)
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// BuildRows produces the recommendation rows for one user.
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//
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// Cost is a handful of Emby queries, which is why callers cache the result rather than
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// computing it on every home load.
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func (e *Engine) BuildRows(ctx context.Context, cred emby.Credentials) ([]Row, error) {
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history, favorites, err := e.gatherSignals(ctx, cred)
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if err != nil {
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return nil, err
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}
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profile := BuildProfile(history, favorites)
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if profile.IsEmpty() {
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// A brand-new user has nothing to recommend from. No rows is the honest answer.
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return nil, nil
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}
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rows := make([]Row, 0, e.MaxSimilarRows+1)
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for _, seed := range e.seedsFor(profile) {
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row, ok := e.similarRow(ctx, cred, profile, seed)
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if ok {
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rows = append(rows, row)
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}
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}
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if row, ok := e.historyRow(ctx, cred, profile); ok {
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rows = append(rows, row)
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}
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return rows, nil
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}
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// gatherSignals reads what the user has watched and favourited, in parallel.
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func (e *Engine) gatherSignals(ctx context.Context, cred emby.Credentials) (history, favorites []Item, err error) {
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var (
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wg sync.WaitGroup
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mu sync.Mutex
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firstErr error
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)
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fetch := func(dest *[]Item, params url.Values) {
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wg.Add(1)
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go func() {
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defer wg.Done()
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result, fetchErr := e.source.Items(ctx, cred, params)
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mu.Lock()
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defer mu.Unlock()
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if fetchErr != nil {
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if firstErr == nil {
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firstErr = fetchErr
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}
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return
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}
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*dest = Decode(result.Items)
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}()
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}
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// In-progress titles are the strongest signal available, so they lead the history
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// list and pick up the heaviest recency weights.
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var resumable, played []Item
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fetch(&resumable, url.Values{
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"Filters": {"IsResumable"},
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"IncludeItemTypes": {"Movie,Episode"},
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"Recursive": {"true"},
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"SortBy": {"DatePlayed"},
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"SortOrder": {"Descending"},
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"Limit": {"20"},
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"Fields": {historyFields},
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"EnableUserData": {"true"},
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"EnableImages": {"false"},
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})
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fetch(&played, url.Values{
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"Filters": {"IsPlayed"},
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"IncludeItemTypes": {"Movie,Episode"},
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"Recursive": {"true"},
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"SortBy": {"DatePlayed"},
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"SortOrder": {"Descending"},
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"Limit": {"60"},
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"Fields": {historyFields},
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"EnableUserData": {"true"},
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"EnableImages": {"false"},
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})
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fetch(&favorites, url.Values{
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"Filters": {"IsFavorite"},
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"IncludeItemTypes": {"Movie,Series"},
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"Recursive": {"true"},
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"SortBy": {"SortName"},
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"Limit": {"40"},
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"Fields": {historyFields},
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"EnableUserData": {"true"},
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"EnableImages": {"false"},
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})
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wg.Wait()
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if firstErr != nil {
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return nil, nil, firstErr
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}
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return append(resumable, played...), favorites, nil
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}
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// libraryCandidates reads the pool from the imported library. Returns ok=false when
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// there is no library, it is empty, or it errors — every one of which means "ask Emby".
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func (e *Engine) libraryCandidates(ctx context.Context, genres []string) ([]Item, bool) {
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if e.Library == nil {
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return nil, false
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}
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raws, err := e.Library.LibraryCandidates(ctx, genres, e.RowSize*6)
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if err != nil {
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e.log.Warn("library candidates failed; falling back to emby", "error", err)
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return nil, false
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}
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if len(raws) == 0 {
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return nil, false
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}
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return Decode(raws), true
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}
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func (e *Engine) seedsFor(profile Profile) []Seed {
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if len(profile.Seeds) <= e.MaxSimilarRows {
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return profile.Seeds
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}
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return profile.Seeds[:e.MaxSimilarRows]
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}
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// similarRow asks Emby what resembles a title the user just watched. Emby's own
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// similarity scoring beats anything computed here, so this only filters out the seen.
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func (e *Engine) similarRow(ctx context.Context, cred emby.Credentials, profile Profile, seed Seed) (Row, bool) {
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result, err := e.source.Similar(ctx, cred, seed.ID, url.Values{
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"UserId": {cred.UserID},
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"Limit": {strconv.Itoa(e.RowSize * 2)},
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"Fields": {candidateFields},
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"ImageTypeLimit": {"1"},
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"EnableImageTypes": {rowImageTypes},
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"EnableUserData": {"true"},
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})
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if err != nil {
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// One dead row should never sink the home screen.
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e.log.Warn("similar lookup failed", "seed", seed.ID, "error", err)
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return Row{}, false
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}
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items := FilterUnseen(profile, Decode(result.Items), e.RowSize)
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if len(items) < e.MinRowItems {
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return Row{}, false
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}
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return Row{
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ID: "similar:" + seed.ID,
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Title: "Because you watched " + seed.Name,
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Kind: "similar",
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Items: Raws(items),
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}, true
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}
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// historyRow is the genre-affinity row: unwatched titles from the genres the user has
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// been spending time in, ranked by how closely they match the whole profile.
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func (e *Engine) historyRow(ctx context.Context, cred emby.Credentials, profile Profile) (Row, bool) {
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genres := profile.TopGenres(3)
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if len(genres) == 0 {
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return Row{}, false
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}
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if candidates, ok := e.libraryCandidates(ctx, genres); ok {
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items := Rank(profile, candidates, e.RowSize)
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if len(items) < e.MinRowItems {
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return Row{}, false
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}
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return Row{
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ID: "recommended",
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Title: "Recommended from your watching history",
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Kind: "recommended",
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Items: Raws(items),
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}, true
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}
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// Emby treats "|" as OR in a Genres filter, so one query covers every top genre.
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result, err := e.source.Items(ctx, cred, url.Values{
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"IncludeItemTypes": {"Movie,Series"},
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"Recursive": {"true"},
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"Filters": {"IsUnplayed"},
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"Genres": {strings.Join(genres, "|")},
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"SortBy": {"CommunityRating"},
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"SortOrder": {"Descending"},
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"Limit": {"120"},
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"Fields": {candidateFields},
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"ImageTypeLimit": {"1"},
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"EnableImages": {"true"},
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"EnableImageTypes": {rowImageTypes},
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"EnableUserData": {"true"},
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})
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if err != nil {
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e.log.Warn("recommendation candidates failed", "error", err)
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return Row{}, false
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}
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items := Rank(profile, Decode(result.Items), e.RowSize)
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if len(items) < e.MinRowItems {
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return Row{}, false
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}
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return Row{
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ID: "recommended",
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Title: "Recommended from your watching history",
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Kind: "recommended",
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Items: Raws(items),
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}, true
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}
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