Added input validations (`source_frame_count <= 0` or `target_frames_per_loop <= 0`) to `AutoLoopCalculatorLTX` (in `loop.py`), and `AutoLoopCalculator`, `AutoLoopCalculatorWan` (in `video.py`). When conditions are met, a safe default is returned to prevent math domain errors. Also included a new comprehensive unit test suite in `tests/test_loop_calculator.py`.
Adds a new ComfyUI utility node `AudioDurationCalculator` to `tools.py` for
calculating the exact duration of an audio file in seconds. Includes robust
error handling to ensure the input is a valid dictionary and returns a
logging string output to maintain consistency with other tools.
- Introduce `global_step_by_chunk` ghost variable initialized to `False` in `loop.py`
- Set `loop.global_step_by_chunk = True` in `AutoLoopCalculatorTTS` to indicate chunk mode
- Reset `loop.global_step_by_chunk = False` in video calculators (`AutoLoopCalculator`, `AutoLoopCalculatorWan`, `AutoLoopCalculatorLTX`) to ensure state resets
- Update `SessionImageSender.send_image` timeline management to branch logic, using `is_chunk_mode` to calculate progress differently for text chunks versus video frames
This commit replaces the raw regex text-splitting logic in `AutoLoopCalculatorTTS` with an "intelligent buffer" approach. It first splits the text by sentence terminators as before, but now aggregates these smaller segments until they contain a minimum of 5 words.
This prevents TTS models from generating robotic, out-of-context micro-audios when encountering trailing ellipses (`...`) or extremely short phrases, leading to more natural intonation and pacing.
All existing loop and timeline injections are preserved.
Replaced simple paragraph/sentence splitting with advanced regex
to gracefully handle split scenarios involving `.`, `?`, `!`,
quotes, ellipses, and `\n`. Punctuation is correctly retained on
the chunks to assure proper TTS intonation.
Moved `import re` to module level imports.
Replaced destructive `del inputs["on_true"]` and `del inputs["on_false"]` with simple state update `inputs["is_final_cycle"] = is_next_final` to rely on MasterSwitch's native lazy evaluation (`check_lazy_status`), fixing a `NodeInputError` bug during looping.
Update `SequentialLoopTrigger` in `loop.py` to correctly identify
`AutoLoopCalculatorTTS` and set `estimated_chunk` to 1 instead of falling
back to a default of 50. This prevents the trigger from incorrectly guessing
when the final loop occurs and mutating the graph prematurely, which caused
errors during sequential TTS tasks.
Refactors `IncrementalVideoStitcher.stitch` to eliminate in-place assignments
into a pre-allocated empty tensor when loading image frames in parallel, which
caused `RuntimeError: Inplace update to inference tensor outside InferenceMode
is not allowed.` in newer PyTorch versions.
The refactored implementation uses a pure map function to return individual
tensors and concatenates them sequentially using `torch.cat`, remaining thread-safe
and compatible with PyTorch's `InferenceMode`. Security against deserialization
vulnerabilities is preserved by ensuring `weights_only=True` remains when loading
audio caches.
- Implemented unit tests for `extract_and_standardize_audio` in `video.py`.
- Added test case to verify exception handling when `torchaudio.load` fails.
- Expanded coverage to include resampling and channel standardization (mono/multichannel to stereo).
- Followed the repository's clean testing pattern for mocking dependencies and loading code under test.
Merged two sequential loops over `prompt.items()` in `SequentialLoopTrigger.trigger_next` into a single pass.
The first pass now simultaneously finds the `estimated_chunk` from `AutoLoopCalculator` and performs mutations for seeds and loop indices.
`MasterSwitch` mutations are deferred to a small secondary pass after `is_next_final` is calculated using the gathered chunk size.
This change reduces the overhead of iterating over large prompt dictionaries and yielded a ~26.8% performance improvement in synthetic benchmarks.
Added `weights_only=True` to `torch.load()` in `video.py` to prevent insecure deserialization and potential arbitrary code execution via crafted pickle files. This change restricts the unpickler to only load tensors, primitive types, and basic containers, which is sufficient for the audio dictionary being loaded.
This commit introduces a new dropdown to the `AutoLoopCalculatorTTS` node inside `video.py`, allowing text to be split by either "Párrafos (Saltos de línea)" or "Frases (Puntos)". When splitting by sentences, it cleanly preserves the periods to maintain proper intonation in TTS systems. Output pins are renamed (`current_text`, `total_chunks`) for better semantics.
- Created tests/test_vram_node.py
- Mocked dependencies (torch, comfy) to allow testing in isolation
- Implemented test cases for zero values, exact GB, fractional values, small values (rounding check), and large values.
- Verified test robustness by confirming failure when logic was intentionally altered.
Replaces the shell-based subprocess call with list-based arguments and
separate invocations for 'apt-get update' and 'apt-get install'.
This eliminates the risk of command injection by avoiding shell
interpretation and properly handles the DEBIAN_FRONTEND environment
variable via sudo.
Introduced concurrent image loading and processing in the Video Stitcher node
using ThreadPoolExecutor. This optimizes the transition from disk-cached PNGs
to the final video tensor by parallelizing I/O and color conversion.
- Replaced sequential loop with ThreadPoolExecutor.map
- Wrapped executor.map in list() to ensure exception propagation
- Verified ~85% speedup in mocked I/O-bound benchmarks
- Registered `AutoLoopCalculatorTTS` in `NODE_DISPLAY_NAME_MAPPINGS`.
- Added `AutoLoopCalculatorTTS` class to `video.py` to allow looping through text paragraphs instead of video frames.
- Replaced the implementation of `IncrementalVideoStitcher` to cache audio tensors as `.pt` files and concatenate them along the time axis on the final cycle.
- Introduced `standardize_video_file` helper in `video.py`.
- The helper creates a physical video clone via FFmpeg, copying the video stream exactly to retain quality while limiting the audio stream.
- Audio limits are conditionally applied using `torchaudio.info` (<=44100Hz and <=2 Channels) to avoid unnecessary processing.
- Implemented a "Fail-Fast" approach with `raise Exception` if the FFmpeg cloning process fails, preventing silent downstream crashes.
- Injected the helper directly into `VideoAnalyzerFaceDetector` and `VideoAnalyzerSceneDetector` to secure the path passed down to VHS.
- Created `extract_and_standardize_audio` helper in `video.py` to standardize audio to 44100Hz and Stereo format.
- Refactored `VideoAnalyzerFaceDetector` and `VideoAnalyzerSceneDetector` to use the new helper function.
- Permanently deleted `modify_facedetector.py`, `modify_facedetector2.py`, and `modify_facedetector3.py` residual scripts.
- Renamed `VideoAnalyzerWithAudio` to `VideoAnalyzerFaceDetector`.
- Introduced `VIDEO_ANALYSIS_CACHE` and `current_loop_index` for cycle caching.
- Created `VideoAnalyzerSceneDetector` to detect scene changes via pixel difference.
- Added dynamic reference frame preview functionality outside the caching logic.
- Registered nodes with proper display names in `__init__.py`.
- Moved `value_in` to the `optional` group to allow ComfyUI to defer its evaluation.
- Updated `check_lazy_status` to return an empty list `[]` for loops > 0, completely cutting off upstream execution.
- Retained the `GLOBAL_SESSION_CACHE` logic scoped by `unique_id`.
- Removed `@register_node` decorator to prevent duplicate registry issues since mapping is handled in `__init__.py`.
Adds a PrimitiveDelay custom node to tools.py that blocks execution for a user-configurable number of seconds, acting as a passthrough using the global `AnyType` wildcard connection. This allows users to throttle rapid API requests, wait for IO tasks to complete, or generally space out ComfyUI execution times in sequential batcher workflows. Re-uses the existing AnyType instance from switch_node.py to adhere to DRY principles.
Adds the LazySessionCache node to `switch_node.py` with lazy evaluation.
It intercepts and stores the input value in cycle 0 and bypasses upstream
evaluation in subsequent loops. Updates `__init__.py` to map the class
and register its display name cleanly.
This commit addresses two primary requests:
1. Replaces all console log prefixes `[DEBUG]` (and variations) with `[Secuencial Batcher]`.
2. Extends the `RETURN_TYPES` and `RETURN_NAMES` of all nodes to output a `log` string containing exactly the text emitted via `print()`. This string is constructed by intercepting `print()` calls inside node methods using a local wrapper and appending the texts to a list, which is then returned joined by newlines.
Meisoftcoltd