fix: set input.options defaults if input.options is none and normalize missing /live prefix for hls streams
fix: document defensive options guard in config input prepare
fix: group configinputoptions methods in one impl
fix: document fallback semantics for configinput _or flag helpers
fix: restore false fallback for missing options in flag checks
Fixed m3u playlist with provider_config persistence as text file
Added probe_delay input option (default 2s); stream probing renamed “Stream Probing” and now covers live, VOD and series as a low‑priority background task.
- Add Makefile to simplify installing required tools
- Add CONTRIBUTING.md welcome new contributors
- Add fmt, lint, test tasks to makefile and update CONTRIBUTING.md
- Add CI workflow
- Log with local date
**Description:**
This PR introduces a major overhaul of how streams are analyzed and connections are managed. It integrates `ffprobe` for deep stream analysis, adds a background task queue for metadata resolution to prevent UI blocking, introduces a connection priority system, and adds support for Live TV probing.
### 🚀 Key Features
* **FFprobe Integration & Live TV Probing**:
* Automatically probes streams (VOD/Series **and now Live TV**) to determine resolution, codecs (HEVC/AV1), dynamic range (HDR/DV), bit depth, and audio channels.
* **Safe Probing**: Probing strictly respects the provider's `max_connections` limit.
* Docker images now include static `ffmpeg/ffprobe` binaries.
* **Smart Connection Management (Priority System)**:
* Introduced a priority system for connections to manage provider limits intelligently.
* **Preemption**: Users with higher priority can preempt (kick) lower priority connections when provider slots are full.
* **Background Queue**: Metadata resolution and stream analysis run as background tasks (Priority 0). They only run when connection slots are idle and yield immediately if a real user needs to stream.
* **Enhanced Metadata Resolution**:
* **Fallback Logic**: If a provider is missing the TMDB ID or Release Date, the system resolves them via the TMDB API.
* **Smart Title Cleaning**: Implemented a centralized cleaner to strip common IPTV prefixes before attempting metadata matches or generating filenames, significantly improving match rates.
* **Improved Output**:
* **Quality Tags**: Filenames in STRM files now include detailed tags (e.g., `Movie - [4K HEVC HDR].strm`).
* **Flat Grouping**: `flat: true` now correctly groups multi-version movies into single folders based on TMDB ID.
* **Global Series Date**: Ensures consistent series folder naming even if episodes have different years.
* Fixed series sort issues
* Playlist explorer copy to clipboard functons implemented
* Epg time fix
* grace period hold stream option added.
* Fixed group and mapper normalization
* Image cache validity for browsers set to 4 hours. Responding now last modified and cache header.
* New Features
Added for_each DSL construct for iterating over playlist item fields, with split() function support.
Added "genre" as a queryable and editable playlist item field.
Bug Fixes
Improved short EPG request handling with automatic default limits.
Fixed EPG timestamp formatting to use UTC consistently.
fixed some logs, added input name
epg short response hos now no errors field
added missing fields for reverse_proxy and library config in ui
fixed button styling
* New Features
Added series information display with episodes, cast, and metadata in playlist explorer
Introduced multi-cluster playlist endpoints (live, VOD, series) for flexible content retrieval
Added series info lookup and filtering capabilities
Implemented sidebar navigation for source editor with dedicated pages (Main, Options, Staged, Advanced, Alias)
Added filter state controls (All, Selected, Deselected) for playlist category management
Enabled Trakt configuration toggle to control integration
Performance Improvements
Optimized B+Tree indexing for faster queries
Reduced startup latency with disk-based operations and optional memory caching
Improved string memory handling through efficient reference-counted strings
UI Enhancements
Enhanced playlist explorer with series details and episode grouping by season
Added new UI icons (Options, Advanced, Staging, Alias, Trakt)
Improved form layouts with toolbar controls
Enhanced radio button group styling for better visual hierarchy
* New Features
Added series information display with episodes, cast, and metadata in playlist explorer
Introduced multi-cluster playlist endpoints (live, VOD, series) for flexible content retrieval
Added series info lookup and filtering capabilities
Implemented sidebar navigation for source editor with dedicated pages (Main, Options, Staged, Advanced, Alias)
Added filter state controls (All, Selected, Deselected) for playlist category management
Enabled Trakt configuration toggle to control integration
Performance Improvements
Optimized B+Tree indexing for faster queries
Reduced startup latency with disk-based operations and optional memory caching
Improved string memory handling through efficient reference-counted strings
UI Enhancements
Enhanced playlist explorer with series details and episode grouping by season
Added new UI icons (Options, Advanced, Staging, Alias, Trakt)
Improved form layouts with toolbar controls
Enhanced radio button group styling for better visual hierarchy
* New Features
Added series information display with episodes, cast, and metadata in playlist explorer
Introduced multi-cluster playlist endpoints (live, VOD, series) for flexible content retrieval
Added series info lookup and filtering capabilities
Implemented sidebar navigation for source editor with dedicated pages (Main, Options, Staged, Advanced, Alias)
Added filter state controls (All, Selected, Deselected) for playlist category management
Enabled Trakt configuration toggle to control integration
Performance Improvements
Optimized B+Tree indexing for faster queries
Reduced startup latency with disk-based operations and optional memory caching
Improved string memory handling through efficient reference-counted strings
UI Enhancements
Enhanced playlist explorer with series details and episode grouping by season
Added new UI icons (Options, Advanced, Staging, Alias, Trakt)
Improved form layouts with toolbar controls
Enhanced radio button group styling for better visual hierarchy
* New Features
Added series information display with episodes, cast, and metadata in playlist explorer
Introduced multi-cluster playlist endpoints (live, VOD, series) for flexible content retrieval
Added series info lookup and filtering capabilities
Implemented sidebar navigation for source editor with dedicated pages (Main, Options, Staged, Advanced, Alias)
Added filter state controls (All, Selected, Deselected) for playlist category management
Enabled Trakt configuration toggle to control integration
Performance Improvements
Optimized B+Tree indexing for faster queries
Reduced startup latency with disk-based operations and optional memory caching
Improved string memory handling through efficient reference-counted strings
UI Enhancements
Enhanced playlist explorer with series details and episode grouping by season
Added new UI icons (Options, Advanced, Staging, Alias, Trakt)
Improved form layouts with toolbar controls
Enhanced radio button group styling for better visual hierarchy
- Added user_agent configuration field to Trakt API settings.
Changes
- Renamed Trakt API configuration field from key to api_key for consistency.
- Updated README and documentation with new Trakt API configuration structure.
- Updated UI labels for API configuration fields.
An optimization has been introduced to reduce memory consumption during playlist updates.
Overview
Previously, provider playlists were fully loaded into memory during the update process. For large playlists (e.g. hundreds of thousands of entries or multiple providers), this could result in significant RAM usage.
With the new implementation, it is now possible to optionally read provider playlists directly from disk instead of keeping them entirely in memory.
How It Works
- users can configure whether:
- Provider playlists are loaded into memory (previous behavior), or
- Provider playlists are streamed to/from disk to minimize RAM usage.
Processing remains sequential and batch-based, ensuring identical functional behavior.
This approach significantly lowers peak memory usage, especially on systems with limited resources.
Benefits
- Reduced peak RAM consumption during playlist updates
- Better scalability for large playlists and multiple providers
- Full backward compatibility
Trade-offs / Drawbacks
- Increased processing time due to reduced in-memory caching
- Higher disk I/O usage, especially for large or fragmented playlists
- Performance depends more strongly on disk speed (Nvme SSD, HDD)
- Slightly increased CPU overhead due to repeated parsing and deserialization
- Not optimal for environments where fast updates are more important than memory usage
Recommendation
- Use in-memory mode for systems with sufficient RAM and a focus on update speed
- Use disk-based mode for large playlists, multiple providers, or memory-constrained environments
An optimization has been introduced to reduce memory consumption during playlist updates.
Overview
Previously, provider playlists were fully loaded into memory during the update process. For large playlists (e.g. hundreds of thousands of entries or multiple providers), this could result in significant RAM usage.
With the new implementation, it is now possible to optionally read provider playlists directly from disk instead of keeping them entirely in memory.
How It Works
- users can configure whether:
- Provider playlists are loaded into memory (previous behavior), or
- Provider playlists are streamed to/from disk to minimize RAM usage.
Processing remains sequential and batch-based, ensuring identical functional behavior.
This approach significantly lowers peak memory usage, especially on systems with limited resources.
Benefits
- Reduced peak RAM consumption during playlist updates
- Better scalability for large playlists and multiple providers
- Full backward compatibility
Trade-offs / Drawbacks
- Increased processing time due to reduced in-memory caching
- Higher disk I/O usage, especially for large or fragmented playlists
- Performance depends more strongly on disk speed (Nvme SSD, HDD)
- Slightly increased CPU overhead due to repeated parsing and deserialization
- Not optimal for environments where fast updates are more important than memory usage
Recommendation
- Use in-memory mode for systems with sufficient RAM and a focus on update speed
- Use disk-based mode for large playlists, multiple providers, or memory-constrained environments
An optimization has been introduced to reduce memory consumption during playlist updates.
Overview
Previously, provider playlists were fully loaded into memory during the update process. For large playlists (e.g. hundreds of thousands of entries or multiple providers), this could result in significant RAM usage.
With the new implementation, it is now possible to optionally read provider playlists directly from disk instead of keeping them entirely in memory.
How It Works
- users can configure whether:
- Provider playlists are loaded into memory (previous behavior), or
- Provider playlists are streamed to/from disk to minimize RAM usage.
Processing remains sequential and batch-based, ensuring identical functional behavior.
This approach significantly lowers peak memory usage, especially on systems with limited resources.
Benefits
- Reduced peak RAM consumption during playlist updates
- Better scalability for large playlists and multiple providers
- Full backward compatibility
Trade-offs / Drawbacks
- Increased processing time due to reduced in-memory caching
- Higher disk I/O usage, especially for large or fragmented playlists
- Performance depends more strongly on disk speed (Nvme SSD, HDD)
- Slightly increased CPU overhead due to repeated parsing and deserialization
- Not optimal for environments where fast updates are more important than memory usage
Recommendation
- Use in-memory mode for systems with sufficient RAM and a focus on update speed
- Use disk-based mode for large playlists, multiple providers, or memory-constrained environments
