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fix: download progress tracking for all engines and inline progress UI

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- Add HFProgressTracker to LuxTTS and Chatterbox backends so tqdm-based
  file-level download progress reaches the frontend (previously only Qwen
  had this, LuxTTS/Chatterbox showed a static spinner)
- Add progress/current/total/filename fields to ActiveDownloadTask so the
  /tasks/active polling endpoint carries progress data
- Show inline progress bar + bytes in the model list and detail modal,
  poll at 1s during active downloads (5s otherwise)
- Fix GpuAcceleration crash: cudaStatusLoading was referenced before
  initialization in its own useQuery declaration
This commit is contained in:
James Pine
2026-03-13 02:09:32 -07:00
parent 9beb9d7fec
commit cc07d4d3c9
7 changed files with 142 additions and 49 deletions
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backend/backends/chatterbox_backend.py
+29 -18
View File
@@ -103,19 +103,27 @@ class ChatterboxTTSBackend:
def _load_model_sync(self):
"""Synchronous model loading."""
from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
progress_manager = get_progress_manager()
task_manager = get_task_manager()
model_name = "chatterbox-tts"
is_cached = self._is_model_cached()
# Set up HF progress tracking (intercepts tqdm for file-level progress)
progress_callback = create_hf_progress_callback(model_name, progress_manager)
tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
tracker_context = tracker.patch_download()
tracker_context.__enter__()
if not is_cached:
task_manager.start_download(model_name)
progress_manager.update_progress(
model_name=model_name,
current=0,
total=0,
filename="Downloading Chatterbox model...",
filename="Connecting to HuggingFace...",
status="downloading",
)
@@ -131,25 +139,28 @@ class ChatterboxTTSBackend:
# Monkey-patch torch.load for CPU loading. The model's .pt files
# were saved on CUDA; from_pretrained() doesn't pass map_location
# so loading on CPU fails without this.
if device == "cpu":
_orig_torch_load = torch.load
try:
if device == "cpu":
_orig_torch_load = torch.load
def _patched_load(*args, **kwargs):
kwargs.setdefault("map_location", "cpu")
return _orig_torch_load(*args, **kwargs)
def _patched_load(*args, **kwargs):
kwargs.setdefault("map_location", "cpu")
return _orig_torch_load(*args, **kwargs)
with ChatterboxTTSBackend._load_lock:
torch.load = _patched_load
try:
self.model = ChatterboxMultilingualTTS.from_pretrained(
device=device,
)
finally:
torch.load = _orig_torch_load
else:
self.model = ChatterboxMultilingualTTS.from_pretrained(
device=device,
)
with ChatterboxTTSBackend._load_lock:
torch.load = _patched_load
try:
self.model = ChatterboxMultilingualTTS.from_pretrained(
device=device,
)
finally:
torch.load = _orig_torch_load
else:
self.model = ChatterboxMultilingualTTS.from_pretrained(
device=device,
)
finally:
tracker_context.__exit__(None, None, None)
# Fix: transformers >= 4.36 defaults LlamaModel to sdpa attention
# which doesn't support output_attentions=True (needed by