Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use vidfom/Ltx-3 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="vidfom/Ltx-3", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-qat-UD-Q4_K_XL.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use vidfom/Ltx-3 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use Docker
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use vidfom/Ltx-3 with Ollama:
ollama run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Unsloth Studio
How to use vidfom/Ltx-3 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for vidfom/Ltx-3 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for vidfom/Ltx-3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vidfom/Ltx-3 to start chatting
- Docker Model Runner
How to use vidfom/Ltx-3 with Docker Model Runner:
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Lemonade
How to use vidfom/Ltx-3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vidfom/Ltx-3:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Ltx-3-UD-Q4_K_XL
List all available models
lemonade list
File size: 22,300 Bytes
e00eceb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 | """Unit tests for comfy_execution/jobs.py"""
from comfy_execution.jobs import (
JobStatus,
is_previewable,
normalize_queue_item,
normalize_history_item,
normalize_output_item,
normalize_outputs,
get_outputs_summary,
apply_sorting,
has_3d_extension,
)
class TestJobStatus:
"""Test JobStatus constants."""
def test_status_values(self):
"""Status constants should have expected string values."""
assert JobStatus.PENDING == 'pending'
assert JobStatus.IN_PROGRESS == 'in_progress'
assert JobStatus.COMPLETED == 'completed'
assert JobStatus.FAILED == 'failed'
assert JobStatus.CANCELLED == 'cancelled'
def test_all_contains_all_statuses(self):
"""ALL should contain all status values."""
assert JobStatus.PENDING in JobStatus.ALL
assert JobStatus.IN_PROGRESS in JobStatus.ALL
assert JobStatus.COMPLETED in JobStatus.ALL
assert JobStatus.FAILED in JobStatus.ALL
assert JobStatus.CANCELLED in JobStatus.ALL
assert len(JobStatus.ALL) == 5
class TestIsPreviewable:
"""Unit tests for is_previewable()"""
def test_previewable_media_types(self):
"""Images, video, audio, 3d, text media types should be previewable."""
for media_type in ['images', 'video', 'audio', '3d', 'text']:
assert is_previewable(media_type, {}) is True
def test_non_previewable_media_types(self):
"""Other media types should not be previewable."""
for media_type in ['latents', 'metadata', 'files']:
assert is_previewable(media_type, {}) is False
def test_3d_extensions_previewable(self):
"""3D file extensions should be previewable regardless of media_type."""
for ext in ['.obj', '.fbx', '.gltf', '.glb', '.usdz']:
item = {'filename': f'model{ext}'}
assert is_previewable('files', item) is True
def test_3d_extensions_case_insensitive(self):
"""3D extension check should be case insensitive."""
item = {'filename': 'MODEL.GLB'}
assert is_previewable('files', item) is True
def test_video_format_previewable(self):
"""Items with video/ format should be previewable."""
item = {'format': 'video/mp4'}
assert is_previewable('files', item) is True
def test_audio_format_previewable(self):
"""Items with audio/ format should be previewable."""
item = {'format': 'audio/wav'}
assert is_previewable('files', item) is True
def test_other_format_not_previewable(self):
"""Items with other format should not be previewable."""
item = {'format': 'application/json'}
assert is_previewable('files', item) is False
class TestGetOutputsSummary:
"""Unit tests for get_outputs_summary()"""
def test_empty_outputs(self):
"""Empty outputs should return 0 count and None preview."""
count, preview = get_outputs_summary({})
assert count == 0
assert preview is None
def test_counts_across_multiple_nodes(self):
"""Outputs from multiple nodes should all be counted."""
outputs = {
'node1': {'images': [{'filename': 'a.png', 'type': 'output'}]},
'node2': {'images': [{'filename': 'b.png', 'type': 'output'}]},
'node3': {'images': [
{'filename': 'c.png', 'type': 'output'},
{'filename': 'd.png', 'type': 'output'}
]}
}
count, preview = get_outputs_summary(outputs)
assert count == 4
def test_skips_animated_key_and_non_list_values(self):
"""The 'animated' key and non-list values should be skipped."""
outputs = {
'node1': {
'images': [{'filename': 'test.png', 'type': 'output'}],
'animated': [True], # Should skip due to key name
'metadata': 'string', # Should skip due to non-list
'count': 42 # Should skip due to non-list
}
}
count, preview = get_outputs_summary(outputs)
assert count == 1
def test_preview_prefers_type_output(self):
"""Items with type='output' should be preferred for preview."""
outputs = {
'node1': {
'images': [
{'filename': 'temp.png', 'type': 'temp'},
{'filename': 'output.png', 'type': 'output'}
]
}
}
count, preview = get_outputs_summary(outputs)
assert count == 2
assert preview['filename'] == 'output.png'
def test_preview_fallback_when_no_output_type(self):
"""If no type='output', should use first previewable."""
outputs = {
'node1': {
'images': [
{'filename': 'temp1.png', 'type': 'temp'},
{'filename': 'temp2.png', 'type': 'temp'}
]
}
}
count, preview = get_outputs_summary(outputs)
assert preview['filename'] == 'temp1.png'
def test_non_previewable_media_types_counted_but_no_preview(self):
"""Non-previewable media types should be counted but not used as preview."""
outputs = {
'node1': {
'latents': [
{'filename': 'latent1.safetensors'},
{'filename': 'latent2.safetensors'}
]
}
}
count, preview = get_outputs_summary(outputs)
assert count == 2
assert preview is None
def test_previewable_media_types(self):
"""Images, video, and audio media types should be previewable."""
for media_type in ['images', 'video', 'audio']:
outputs = {
'node1': {
media_type: [{'filename': 'test.file', 'type': 'output'}]
}
}
count, preview = get_outputs_summary(outputs)
assert preview is not None, f"{media_type} should be previewable"
def test_3d_files_previewable(self):
"""3D file extensions should be previewable."""
for ext in ['.obj', '.fbx', '.gltf', '.glb', '.usdz']:
outputs = {
'node1': {
'files': [{'filename': f'model{ext}', 'type': 'output'}]
}
}
count, preview = get_outputs_summary(outputs)
assert preview is not None, f"3D file {ext} should be previewable"
def test_format_mime_type_previewable(self):
"""Files with video/ or audio/ format should be previewable."""
for fmt in ['video/x-custom', 'audio/x-custom']:
outputs = {
'node1': {
'files': [{'filename': 'file.custom', 'format': fmt, 'type': 'output'}]
}
}
count, preview = get_outputs_summary(outputs)
assert preview is not None, f"Format {fmt} should be previewable"
def test_preview_enriched_with_node_metadata(self):
"""Preview should include nodeId, mediaType, and original fields."""
outputs = {
'node123': {
'images': [{'filename': 'test.png', 'type': 'output', 'subfolder': 'outputs'}]
}
}
count, preview = get_outputs_summary(outputs)
assert preview['nodeId'] == 'node123'
assert preview['mediaType'] == 'images'
assert preview['subfolder'] == 'outputs'
def test_string_3d_filename_creates_preview(self):
"""String items with 3D extensions should synthesize a preview (Preview3D node output).
Only the .glb counts — nulls and non-file strings are excluded."""
outputs = {
'node1': {
'result': ['preview3d_abc123.glb', None, None]
}
}
count, preview = get_outputs_summary(outputs)
assert count == 1
assert preview is not None
assert preview['filename'] == 'preview3d_abc123.glb'
assert preview['mediaType'] == '3d'
assert preview['nodeId'] == 'node1'
assert preview['type'] == 'output'
def test_string_non_3d_filename_no_preview(self):
"""String items without 3D extensions should not create a preview."""
outputs = {
'node1': {
'result': ['data.json', None]
}
}
count, preview = get_outputs_summary(outputs)
assert count == 0
assert preview is None
def test_string_3d_filename_used_as_fallback(self):
"""String 3D preview should be used when no dict items are previewable."""
outputs = {
'node1': {
'latents': [{'filename': 'latent.safetensors'}],
},
'node2': {
'result': ['model.glb', None]
}
}
count, preview = get_outputs_summary(outputs)
assert preview is not None
assert preview['filename'] == 'model.glb'
assert preview['mediaType'] == '3d'
class TestHas3DExtension:
"""Unit tests for has_3d_extension()"""
def test_recognized_extensions(self):
for ext in ['.obj', '.fbx', '.gltf', '.glb', '.usdz']:
assert has_3d_extension(f'model{ext}') is True
def test_case_insensitive(self):
assert has_3d_extension('MODEL.GLB') is True
assert has_3d_extension('Scene.GLTF') is True
def test_non_3d_extensions(self):
for name in ['photo.png', 'video.mp4', 'data.json', 'model']:
assert has_3d_extension(name) is False
class TestApplySorting:
"""Unit tests for apply_sorting()"""
def test_sort_by_create_time_desc(self):
"""Default sort by create_time descending."""
jobs = [
{'id': 'a', 'create_time': 100},
{'id': 'b', 'create_time': 300},
{'id': 'c', 'create_time': 200},
]
result = apply_sorting(jobs, 'created_at', 'desc')
assert [j['id'] for j in result] == ['b', 'c', 'a']
def test_sort_by_create_time_asc(self):
"""Sort by create_time ascending."""
jobs = [
{'id': 'a', 'create_time': 100},
{'id': 'b', 'create_time': 300},
{'id': 'c', 'create_time': 200},
]
result = apply_sorting(jobs, 'created_at', 'asc')
assert [j['id'] for j in result] == ['a', 'c', 'b']
def test_sort_by_execution_duration(self):
"""Sort by execution_duration should order by duration."""
jobs = [
{'id': 'a', 'create_time': 100, 'execution_start_time': 100, 'execution_end_time': 5100}, # 5s
{'id': 'b', 'create_time': 300, 'execution_start_time': 300, 'execution_end_time': 1300}, # 1s
{'id': 'c', 'create_time': 200, 'execution_start_time': 200, 'execution_end_time': 3200}, # 3s
]
result = apply_sorting(jobs, 'execution_duration', 'desc')
assert [j['id'] for j in result] == ['a', 'c', 'b']
def test_sort_with_none_values(self):
"""Jobs with None values should sort as 0."""
jobs = [
{'id': 'a', 'create_time': 100, 'execution_start_time': 100, 'execution_end_time': 5100},
{'id': 'b', 'create_time': 300, 'execution_start_time': None, 'execution_end_time': None},
{'id': 'c', 'create_time': 200, 'execution_start_time': 200, 'execution_end_time': 3200},
]
result = apply_sorting(jobs, 'execution_duration', 'asc')
assert result[0]['id'] == 'b' # None treated as 0, comes first
class TestNormalizeQueueItem:
"""Unit tests for normalize_queue_item()"""
def test_basic_normalization(self):
"""Queue item should be normalized to job dict."""
item = (
10, # priority/number
'prompt-123', # prompt_id
{'nodes': {}}, # prompt
{
'create_time': 1234567890,
'extra_pnginfo': {'workflow': {'id': 'workflow-abc'}}
}, # extra_data
['node1'], # outputs_to_execute
)
job = normalize_queue_item(item, JobStatus.PENDING)
assert job['id'] == 'prompt-123'
assert job['status'] == 'pending'
assert job['priority'] == 10
assert job['create_time'] == 1234567890
assert 'execution_start_time' not in job
assert 'execution_end_time' not in job
assert 'execution_error' not in job
assert 'preview_output' not in job
assert job['outputs_count'] == 0
assert job['workflow_id'] == 'workflow-abc'
class TestNormalizeHistoryItem:
"""Unit tests for normalize_history_item()"""
def test_completed_job(self):
"""Completed history item should have correct status and times from messages."""
history_item = {
'prompt': (
5, # priority
'prompt-456',
{'nodes': {}},
{
'create_time': 1234567890000,
'extra_pnginfo': {'workflow': {'id': 'workflow-xyz'}}
},
['node1'],
),
'status': {
'status_str': 'success',
'completed': True,
'messages': [
('execution_start', {'prompt_id': 'prompt-456', 'timestamp': 1234567890500}),
('execution_success', {'prompt_id': 'prompt-456', 'timestamp': 1234567893000}),
]
},
'outputs': {},
}
job = normalize_history_item('prompt-456', history_item)
assert job['id'] == 'prompt-456'
assert job['status'] == 'completed'
assert job['priority'] == 5
assert job['execution_start_time'] == 1234567890500
assert job['execution_end_time'] == 1234567893000
assert job['workflow_id'] == 'workflow-xyz'
def test_failed_job(self):
"""Failed history item should have failed status and error from messages."""
history_item = {
'prompt': (
5,
'prompt-789',
{'nodes': {}},
{'create_time': 1234567890000},
['node1'],
),
'status': {
'status_str': 'error',
'completed': False,
'messages': [
('execution_start', {'prompt_id': 'prompt-789', 'timestamp': 1234567890500}),
('execution_error', {
'prompt_id': 'prompt-789',
'node_id': '5',
'node_type': 'KSampler',
'exception_message': 'CUDA out of memory',
'exception_type': 'RuntimeError',
'traceback': ['Traceback...', 'RuntimeError: CUDA out of memory'],
'timestamp': 1234567891000,
})
]
},
'outputs': {},
}
job = normalize_history_item('prompt-789', history_item)
assert job['status'] == 'failed'
assert job['execution_start_time'] == 1234567890500
assert job['execution_end_time'] == 1234567891000
assert job['execution_error']['node_id'] == '5'
assert job['execution_error']['node_type'] == 'KSampler'
assert job['execution_error']['exception_message'] == 'CUDA out of memory'
def test_cancelled_job(self):
"""Cancelled/interrupted history item should have cancelled status."""
history_item = {
'prompt': (
5,
'prompt-cancelled',
{'nodes': {}},
{'create_time': 1234567890000},
['node1'],
),
'status': {
'status_str': 'error',
'completed': False,
'messages': [
('execution_start', {'prompt_id': 'prompt-cancelled', 'timestamp': 1234567890500}),
('execution_interrupted', {
'prompt_id': 'prompt-cancelled',
'node_id': '5',
'node_type': 'KSampler',
'executed': ['1', '2', '3'],
'timestamp': 1234567891000,
})
]
},
'outputs': {},
}
job = normalize_history_item('prompt-cancelled', history_item)
assert job['status'] == 'cancelled'
assert job['execution_start_time'] == 1234567890500
assert job['execution_end_time'] == 1234567891000
# Cancelled jobs should not have execution_error set
assert 'execution_error' not in job
def test_include_outputs(self):
"""When include_outputs=True, should include full output data."""
history_item = {
'prompt': (
5,
'prompt-123',
{'nodes': {'1': {}}},
{'create_time': 1234567890, 'client_id': 'abc'},
['node1'],
),
'status': {'status_str': 'success', 'completed': True, 'messages': []},
'outputs': {'node1': {'images': [{'filename': 'test.png'}]}},
}
job = normalize_history_item('prompt-123', history_item, include_outputs=True)
assert 'outputs' in job
assert 'workflow' in job
assert 'execution_status' in job
assert job['outputs'] == {'node1': {'images': [{'filename': 'test.png'}]}}
assert job['workflow'] == {
'prompt': {'nodes': {'1': {}}},
'extra_data': {'create_time': 1234567890, 'client_id': 'abc'},
}
def test_include_outputs_normalizes_3d_strings(self):
"""Detail view should transform string 3D filenames into file output dicts."""
history_item = {
'prompt': (
5,
'prompt-3d',
{'nodes': {}},
{'create_time': 1234567890},
['node1'],
),
'status': {'status_str': 'success', 'completed': True, 'messages': []},
'outputs': {
'node1': {
'result': ['preview3d_abc123.glb', None, None]
}
},
}
job = normalize_history_item('prompt-3d', history_item, include_outputs=True)
assert job['outputs_count'] == 1
result_items = job['outputs']['node1']['result']
assert len(result_items) == 1
assert result_items[0] == {
'filename': 'preview3d_abc123.glb',
'type': 'output',
'subfolder': '',
'mediaType': '3d',
}
def test_include_outputs_preserves_dict_items(self):
"""Detail view normalization should pass dict items through unchanged."""
history_item = {
'prompt': (
5,
'prompt-img',
{'nodes': {}},
{'create_time': 1234567890},
['node1'],
),
'status': {'status_str': 'success', 'completed': True, 'messages': []},
'outputs': {
'node1': {
'images': [
{'filename': 'photo.png', 'type': 'output', 'subfolder': ''},
]
}
},
}
job = normalize_history_item('prompt-img', history_item, include_outputs=True)
assert job['outputs_count'] == 1
assert job['outputs']['node1']['images'] == [
{'filename': 'photo.png', 'type': 'output', 'subfolder': ''},
]
class TestNormalizeOutputItem:
"""Unit tests for normalize_output_item()"""
def test_none_returns_none(self):
assert normalize_output_item(None) is None
def test_string_3d_extension_synthesizes_dict(self):
result = normalize_output_item('model.glb')
assert result == {'filename': 'model.glb', 'type': 'output', 'subfolder': '', 'mediaType': '3d'}
def test_string_non_3d_extension_returns_none(self):
assert normalize_output_item('data.json') is None
def test_string_no_extension_returns_none(self):
assert normalize_output_item('camera_info_string') is None
def test_dict_passes_through(self):
item = {'filename': 'test.png', 'type': 'output'}
assert normalize_output_item(item) is item
def test_other_types_return_none(self):
assert normalize_output_item(42) is None
assert normalize_output_item(True) is None
class TestNormalizeOutputs:
"""Unit tests for normalize_outputs()"""
def test_empty_outputs(self):
assert normalize_outputs({}) == {}
def test_dict_items_pass_through(self):
outputs = {
'node1': {
'images': [{'filename': 'a.png', 'type': 'output'}],
}
}
result = normalize_outputs(outputs)
assert result == outputs
def test_3d_string_synthesized(self):
outputs = {
'node1': {
'result': ['model.glb', None, None],
}
}
result = normalize_outputs(outputs)
assert result == {
'node1': {
'result': [
{'filename': 'model.glb', 'type': 'output', 'subfolder': '', 'mediaType': '3d'},
],
}
}
def test_animated_key_preserved(self):
outputs = {
'node1': {
'images': [{'filename': 'a.png', 'type': 'output'}],
'animated': [True],
}
}
result = normalize_outputs(outputs)
assert result['node1']['animated'] == [True]
def test_non_dict_node_outputs_preserved(self):
outputs = {'node1': 'unexpected_value'}
result = normalize_outputs(outputs)
assert result == {'node1': 'unexpected_value'}
def test_none_items_filtered_but_other_types_preserved(self):
outputs = {
'node1': {
'result': ['data.json', None, [1, 2, 3]],
}
}
result = normalize_outputs(outputs)
assert result == {
'node1': {
'result': ['data.json', [1, 2, 3]],
}
}
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