sugarr/test/app/pipelines/RecommendationPipeline.test.ts

import { describe, expect, it, vi } from 'vitest';
import { RecommendationPipeline } from '../../../src/app/pipelines/RecommendationPipeline';
import type { JellyfinClient } from '../../../src/app/clients/jellyfin/JellyfinClient';
import type { TmdbClient } from '../../../src/app/clients/tmdb/TmdbClient';
import type { RadarrClient } from '../../../src/app/clients/radarr/RadarrClient';
import type { MovieRecommenderTool } from '../../../src/app/tools/MovieRecommenderTool';
import type { MovieSearchTool } from '../../../src/app/tools/MovieSearchTool';
import type { Movie, TMDbMovie } from '../../../src/app/models';
import type { Tracer, TraceHandle } from '../../../src/core/llm/Tracer';
import type { Logger } from '../../../src/core/logging/logger';

const movie = (name: string, year: number, tmdbId: string): Movie => ({
  name,
  year,
  imdbId: '',
  tmdbId,
  genres: [],
  communityRating: 0,
  isFavorite: false,
  playCount: 0,
});

function makeTracer() {
  const trace = { id: 'trace-1', startGeneration: vi.fn() } as unknown as TraceHandle;
  const tracer = {
    startTrace: vi.fn().mockReturnValue(trace),
    flush: vi.fn().mockResolvedValue(undefined),
  } as unknown as Tracer;
  return tracer;
}

describe('RecommendationPipeline.runAsync', () => {
  it('uses favorites as the signal when there are enough, resolves suggestions via TMDb, and excludes library/Radarr matches', async () => {
    const jellyfin = {
      getFavoriteMovies: vi.fn().mockResolvedValue([movie('Dune', 2021, '1')]),
      getRecentlyWatched: vi.fn(),
      getAllMovies: vi.fn().mockResolvedValue([movie('Arrival', 2016, '2')]),
    } as unknown as JellyfinClient;

    const searchMovie = vi
      .fn()
      .mockResolvedValueOnce({ id: 3, title: 'Interstellar', year: 2014 } as TMDbMovie);
    const tmdb = { searchMovie } as unknown as TmdbClient;

    const radarr = {
      getExisting: vi.fn().mockResolvedValue([{ tmdbId: 4 }]),
    } as unknown as RadarrClient;

    const tool = {
      runAsync: vi.fn().mockResolvedValue([{ title: 'Interstellar', year: 2014, reason: 'space epic' }]),
    } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;

    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin,
      tmdb,
      radarr,
      tool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 2,
    });

    const result = await pipeline.runAsync({ count: 1, useLlm: true });

    expect(jellyfin.getRecentlyWatched).not.toHaveBeenCalled();
    expect(result).toEqual([{ title: 'Interstellar', year: 2014, tmdbId: 3, reason: 'space epic' }]);
    expect(tool.runAsync).toHaveBeenCalledWith(
      expect.objectContaining({ favorites: [movie('Dune', 2021, '1')], count: 1 }),
      expect.anything()
    );
  });

  it('falls back to recently-watched as the signal when favorites are below the threshold', async () => {
    const jellyfin = {
      getFavoriteMovies: vi.fn().mockResolvedValue([]),
      getRecentlyWatched: vi.fn().mockResolvedValue([movie('Arrival', 2016, '2')]),
      getAllMovies: vi.fn().mockResolvedValue([]),
    } as unknown as JellyfinClient;
    const tmdb = { searchMovie: vi.fn().mockResolvedValue(undefined) } as unknown as TmdbClient;
    const tool = { runAsync: vi.fn().mockResolvedValue([]) } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;

    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin,
      tmdb,
      tool,
      searchTool,
      minRatedMovies: 5,
      maxRetry: 0,
    });

    await pipeline.runAsync({ count: 1, useLlm: true });

    expect(jellyfin.getRecentlyWatched).toHaveBeenCalled();
    expect(tool.runAsync).toHaveBeenCalledWith(
      expect.objectContaining({ watched: [movie('Arrival', 2016, '2')] }),
      expect.anything()
    );
  });

  it('retries up to maxRetry times, excluding already-suggested movies, until count is reached', async () => {
    const jellyfin = {
      getFavoriteMovies: vi.fn().mockResolvedValue([movie('Dune', 2021, '1')]),
      getRecentlyWatched: vi.fn(),
      getAllMovies: vi.fn().mockResolvedValue([]),
    } as unknown as JellyfinClient;

    const tmdb = {
      searchMovie: vi
        .fn()
        .mockResolvedValueOnce({ id: 10, title: 'AlreadyInLibrary', year: 2000 } as TMDbMovie)
        .mockResolvedValueOnce({ id: 11, title: 'NewPick', year: 2022 } as TMDbMovie),
    } as unknown as TmdbClient;

    const tool = {
      runAsync: vi
        .fn()
        .mockResolvedValueOnce([{ title: 'AlreadyInLibrary', year: 2000, reason: 'r1' }])
        .mockResolvedValueOnce([{ title: 'NewPick', year: 2022, reason: 'r2' }]),
    } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;

    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin,
      tmdb,
      tool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 2,
    });

    // Simulate id 10 already excluded (already in library) by pre-seeding via getAllMovies
    jellyfin.getAllMovies = vi.fn().mockResolvedValue([movie('AlreadyInLibrary', 2000, '10')]);

    const result = await pipeline.runAsync({ count: 1, useLlm: true });

    expect(tool.runAsync).toHaveBeenCalledTimes(2);
    expect(result).toEqual([{ title: 'NewPick', year: 2022, tmdbId: 11, reason: 'r2' }]);
  });

  it('uses the TMDb similarity/frequency fallback when useLlm is false', async () => {
    const jellyfin = {
      getFavoriteMovies: vi.fn().mockResolvedValue([movie('Dune', 2021, '1')]),
      getRecentlyWatched: vi.fn(),
      getAllMovies: vi.fn().mockResolvedValue([]),
    } as unknown as JellyfinClient;

    const tmdb = {
      getSimilar: vi.fn().mockResolvedValue([{ id: 20, title: 'Similar A', year: 2010 } as TMDbMovie]),
      getRecommendations: vi
        .fn()
        .mockResolvedValue([{ id: 20, title: 'Similar A', year: 2010 } as TMDbMovie]),
      searchMovie: vi.fn().mockResolvedValue({ id: 20, title: 'Similar A', year: 2010 } as TMDbMovie),
    } as unknown as TmdbClient;

    const tool = { runAsync: vi.fn() } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;

    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin,
      tmdb,
      tool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    const result = await pipeline.runAsync({ count: 1, useLlm: false });

    expect(tool.runAsync).not.toHaveBeenCalled();
    expect(result).toEqual([{ title: 'Similar A', year: 2010, tmdbId: 20, reason: 'Recommended by TMDb' }]);
  });

  it('continues with an incomplete exclusion set when fetching the library fails', async () => {
    const jellyfin = {
      getFavoriteMovies: vi.fn().mockResolvedValue([movie('Dune', 2021, '1')]),
      getRecentlyWatched: vi.fn(),
      getAllMovies: vi.fn().mockRejectedValue(new Error('jellyfin down')),
    } as unknown as JellyfinClient;
    const tmdb = {
      searchMovie: vi.fn().mockResolvedValue({ id: 3, title: 'Interstellar', year: 2014 } as TMDbMovie),
    } as unknown as TmdbClient;
    const tool = {
      runAsync: vi.fn().mockResolvedValue([{ title: 'Interstellar', year: 2014, reason: 'r' }]),
    } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;
    const logger = { warn: vi.fn() } as unknown as Logger;

    const pipeline = new RecommendationPipeline(makeTracer(), logger, {
      jellyfin,
      tmdb,
      tool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    const result = await pipeline.runAsync({ count: 1, useLlm: true });

    expect(result).toEqual([{ title: 'Interstellar', year: 2014, tmdbId: 3, reason: 'r' }]);
    expect(logger.warn).toHaveBeenCalledWith(
      expect.objectContaining({ err: expect.any(Error) }),
      'Could not fetch library; exclusion may be incomplete'
    );
  });

  it('skips a suggestion whose TMDb resolution fails instead of aborting the run', async () => {
    const jellyfin = {
      getFavoriteMovies: vi.fn().mockResolvedValue([movie('Dune', 2021, '1')]),
      getRecentlyWatched: vi.fn(),
      getAllMovies: vi.fn().mockResolvedValue([]),
    } as unknown as JellyfinClient;
    const tmdb = {
      searchMovie: vi
        .fn()
        .mockRejectedValueOnce(new Error('tmdb down'))
        .mockResolvedValueOnce({ id: 3, title: 'Interstellar', year: 2014 } as TMDbMovie),
    } as unknown as TmdbClient;
    const tool = {
      runAsync: vi.fn().mockResolvedValue([
        { title: 'Unresolvable', year: 1999, reason: 'r1' },
        { title: 'Interstellar', year: 2014, reason: 'r2' },
      ]),
    } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;
    const logger = { warn: vi.fn() } as unknown as Logger;

    const pipeline = new RecommendationPipeline(makeTracer(), logger, {
      jellyfin,
      tmdb,
      tool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    const result = await pipeline.runAsync({ count: 2, useLlm: true });

    expect(result).toEqual([{ title: 'Interstellar', year: 2014, tmdbId: 3, reason: 'r2' }]);
    expect(logger.warn).toHaveBeenCalledWith(
      expect.objectContaining({ err: expect.any(Error), title: 'Unresolvable' }),
      'TMDb search failed, skipping suggestion'
    );
  });

  it('skips a signal movie whose TMDb similar/recommendations lookup fails in the fallback path', async () => {
    const jellyfin = {
      getFavoriteMovies: vi
        .fn()
        .mockResolvedValue([movie('Broken', 2000, '1'), movie('Dune', 2021, '2')]),
      getRecentlyWatched: vi.fn(),
      getAllMovies: vi.fn().mockResolvedValue([]),
    } as unknown as JellyfinClient;
    const tmdb = {
      getSimilar: vi.fn().mockImplementation((id: number) => {
        if (id === 1) return Promise.reject(new Error('tmdb down'));
        return Promise.resolve([{ id: 20, title: 'Similar A', year: 2010 } as TMDbMovie]);
      }),
      getRecommendations: vi.fn().mockImplementation((id: number) => {
        if (id === 1) return Promise.reject(new Error('tmdb down'));
        return Promise.resolve([]);
      }),
      searchMovie: vi.fn().mockResolvedValue({ id: 20, title: 'Similar A', year: 2010 } as TMDbMovie),
    } as unknown as TmdbClient;
    const tool = { runAsync: vi.fn() } as unknown as MovieRecommenderTool;
    const searchTool = { runAsync: vi.fn() } as unknown as MovieSearchTool;
    const logger = { warn: vi.fn() } as unknown as Logger;

    const pipeline = new RecommendationPipeline(makeTracer(), logger, {
      jellyfin,
      tmdb,
      tool,
      searchTool,
      minRatedMovies: 2,
      maxRetry: 0,
    });

    const result = await pipeline.runAsync({ count: 1, useLlm: false });

    expect(result).toEqual([{ title: 'Similar A', year: 2010, tmdbId: 20, reason: 'Recommended by TMDb' }]);
    expect(logger.warn).toHaveBeenCalledWith(
      expect.objectContaining({ err: expect.any(Error), tmdbId: 1 }),
      'TMDb similar/recommendations failed, skipping signal movie'
    );
  });
});

describe('RecommendationPipeline.autoRequest', () => {
  it('looks up and adds each recommendation to Radarr when Radarr is configured', async () => {
    const radarr = {
      lookup: vi.fn().mockResolvedValue({
        title: 'Dune',
        tmdbId: 1,
        qualityProfileId: 1,
        rootFolderPath: '/movies',
        monitored: true,
        addOptions: { searchForMovie: true },
      }),
      addMovie: vi.fn().mockResolvedValue(undefined),
    } as unknown as RadarrClient;

    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin: {} as JellyfinClient,
      tmdb: {} as TmdbClient,
      radarr,
      tool: {} as MovieRecommenderTool,
      searchTool: {} as MovieSearchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    await pipeline.autoRequest([{ title: 'Dune', year: 2021, tmdbId: 1, reason: 'r' }]);

    expect(radarr.lookup).toHaveBeenCalledWith(1);
    expect(radarr.addMovie).toHaveBeenCalled();
  });

  it('does nothing when Radarr is not configured', async () => {
    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin: {} as JellyfinClient,
      tmdb: {} as TmdbClient,
      tool: {} as MovieRecommenderTool,
      searchTool: {} as MovieSearchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    await expect(pipeline.autoRequest([{ title: 'Dune', year: 2021, tmdbId: 1, reason: 'r' }])).resolves.toBeUndefined();
  });

  it('logs and continues when one recommendation fails, instead of aborting the rest', async () => {
    const radarr = {
      lookup: vi
        .fn()
        .mockRejectedValueOnce(new Error('radarr down'))
        .mockResolvedValueOnce({
          title: 'Arrival',
          tmdbId: 2,
          qualityProfileId: 1,
          rootFolderPath: '/movies',
          monitored: true,
          addOptions: { searchForMovie: true },
        }),
      addMovie: vi.fn().mockResolvedValue(undefined),
    } as unknown as RadarrClient;
    const logger = { error: vi.fn() } as unknown as Logger;

    const pipeline = new RecommendationPipeline(makeTracer(), logger, {
      jellyfin: {} as JellyfinClient,
      tmdb: {} as TmdbClient,
      radarr,
      tool: {} as MovieRecommenderTool,
      searchTool: {} as MovieSearchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    await pipeline.autoRequest([
      { title: 'Dune', year: 2021, tmdbId: 1, reason: 'r1' },
      { title: 'Arrival', year: 2016, tmdbId: 2, reason: 'r2' },
    ]);

    expect(logger.error).toHaveBeenCalledWith(
      expect.objectContaining({ tmdbId: 1, title: 'Dune' }),
      'Radarr auto-request failed'
    );
    expect(radarr.lookup).toHaveBeenCalledTimes(2);
    expect(radarr.addMovie).toHaveBeenCalledTimes(1);
  });
});

describe('RecommendationPipeline.searchAsync', () => {
  it('runs the search tool, resolves via TMDb, and excludes library matches', async () => {
    const jellyfin = {
      getAllMovies: vi.fn().mockResolvedValue([movie('AlreadyHave', 1999, '5')]),
    } as unknown as JellyfinClient;
    const tmdb = {
      searchMovie: vi.fn().mockResolvedValue({ id: 6, title: 'New Find', year: 2020 } as TMDbMovie),
    } as unknown as TmdbClient;
    const searchTool = {
      runAsync: vi.fn().mockResolvedValue([{ title: 'New Find', year: 2020, reason: 'matches query' }]),
    } as unknown as MovieSearchTool;

    const pipeline = new RecommendationPipeline(makeTracer(), {} as Logger, {
      jellyfin,
      tmdb,
      tool: {} as MovieRecommenderTool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    const result = await pipeline.searchAsync('sci-fi like Dune', 5);

    expect(result).toEqual([{ title: 'New Find', year: 2020, tmdbId: 6, reason: 'matches query' }]);
    expect(searchTool.runAsync).toHaveBeenCalledWith({ query: 'sci-fi like Dune', count: 5 }, expect.anything());
  });

  it('continues with an empty exclusion set when fetching the library fails', async () => {
    const jellyfin = {
      getAllMovies: vi.fn().mockRejectedValue(new Error('jellyfin down')),
    } as unknown as JellyfinClient;
    const tmdb = {
      searchMovie: vi.fn().mockResolvedValue({ id: 6, title: 'New Find', year: 2020 } as TMDbMovie),
    } as unknown as TmdbClient;
    const searchTool = {
      runAsync: vi.fn().mockResolvedValue([{ title: 'New Find', year: 2020, reason: 'matches query' }]),
    } as unknown as MovieSearchTool;
    const logger = { warn: vi.fn() } as unknown as Logger;

    const pipeline = new RecommendationPipeline(makeTracer(), logger, {
      jellyfin,
      tmdb,
      tool: {} as MovieRecommenderTool,
      searchTool,
      minRatedMovies: 1,
      maxRetry: 0,
    });

    const result = await pipeline.searchAsync('sci-fi like Dune', 5);

    expect(result).toEqual([{ title: 'New Find', year: 2020, tmdbId: 6, reason: 'matches query' }]);
    expect(logger.warn).toHaveBeenCalledWith(
      expect.objectContaining({ err: expect.any(Error) }),
      'Could not fetch library; exclusion may be incomplete'
    );
  });
});