fix(import): polish library import UI and widen cross-promo detection

[ashwkun]

Summary

• Rebuild the OPML/JSON import flow with a shared loader hero that morphs into the success checkmark, plus clearer selector/progress/success screens
• Widen cross-promotion detection with more title patterns, description “subscribe to / check out” cues, and better search match scoring
• Extract import UI out of MainActivity into ui/libraryimport

Test plan

• Open Import Library (onboarding or Settings) and restore a .json backup — confirm loader fills into the checkmark, then Continue
• Import an .opml file — confirm progress UI, optional mark-played step, and success morph
• Open a promo/trailer episode with “subscribe to …” (or similar) in the description and confirm the cross-promo card appears when a show resolves
• Confirm normal non-promo episodes still do not show the card

[coderabbitai]

Caution

Review failed

The pull request is closed.

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: ASSERTIVE

Plan: Pro

Run ID: 4aa4667e-3bc7-4703-8848-87e79a715e5d

📥 Commits

Reviewing files that changed from the base of the PR and between 59d42bf and 74a4327.

📒 Files selected for processing (6)

• app/src/main/java/cx/aswin/boxcast/MainActivity.kt
• app/src/main/java/cx/aswin/boxcast/ui/libraryimport/OpmlImportDialog.kt
• core/data/src/main/java/cx/aswin/boxcast/core/data/crosspromo/CrossPromotionDetector.kt
• core/data/src/main/java/cx/aswin/boxcast/core/data/crosspromo/CrossPromotionResolver.kt
• core/data/src/test/java/cx/aswin/boxcast/core/data/crosspromo/CrossPromotionDetectorTest.kt
• core/model/src/main/java/cx/aswin/boxcast/core/model/CrossPromotion.kt

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📝 Walkthrough

Summary by CodeRabbit

• New Features

  • Added a dedicated library import dialog supporting JSON backups and OPML files.
  • Import flow now includes progress updates, item selection, completion summaries, retry handling, and notification prompts.

• Improvements

  • Improved cross-promotion detection using episode descriptions, additional promotional patterns, and stronger title filtering.
  • Improved podcast matching by scoring multiple search results and ignoring weak or generic matches.

• Tests

  • Added coverage for description-based promotions, guest-feed patterns, and invalid show-name matches.

Walkthrough

The OPML import state model and Compose dialog move into a dedicated library-import file. Cross-promotion detection adds description-based heuristics, stricter name filtering, improved podcast result scoring, a new indicator, and expanded tests.

Changes

Library import UI

Layer / File(s)	Summary
Import state and dialog wiring app/src/main/java/cx/aswin/boxcast/MainActivity.kt, app/src/main/java/cx/aswin/boxcast/ui/libraryimport/OpmlImportDialog.kt	The import state model and dialog entry point move out of MainActivity into the library-import package, with dismissal rules and document picker setup.
Import progress and selection flow app/src/main/java/cx/aswin/boxcast/ui/libraryimport/OpmlImportDialog.kt	The dialog renders animated progress states, JSON and OPML choices, and podcast selection controls for completion handling.
Import completion and error states app/src/main/java/cx/aswin/boxcast/ui/libraryimport/OpmlImportDialog.kt	Success summaries, notification permission handling, summary rows, and error dismissal content are implemented in the extracted dialog.

Cross-promotion detection

Layer / File(s)	Summary
Detection indicators and heuristics core/model/src/main/java/cx/aswin/boxcast/core/model/CrossPromotion.kt, core/data/src/main/java/cx/aswin/boxcast/core/data/crosspromo/CrossPromotionDetector.kt, core/data/src/test/java/cx/aswin/boxcast/core/data/crosspromo/CrossPromotionDetectorTest.kt	Detection adds DESCRIPTION_PROMO_LANGUAGE, description-based show extraction, expanded promo patterns, extracted-name filtering, updated confidence paths, and corresponding tests.
Resolved podcast matching core/data/src/main/java/cx/aswin/boxcast/core/data/crosspromo/CrossPromotionResolver.kt	Resolution handles blank queries and ranks multiple search results using normalized title similarity and token overlap.

Estimated code review effort: 4 (Complex) | ~60 minutes

Suggested labels: user-impact-medium, backend-change

✨ Finishing Touches

📝 Generate docstrings

• Create stacked PR
• Commit on current branch

• 🛠️ update changelog

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[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud