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
- 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 new
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: 6,612 Bytes
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import hashlib
import json
import logging
import os
import re
from typing import Any
import folder_paths
logger = logging.getLogger(__name__)
def get_log_directory():
"""Ensures the API log directory exists within ComfyUI's temp directory and returns its path."""
base_temp_dir = folder_paths.get_temp_directory()
log_dir = os.path.join(base_temp_dir, "api_logs")
try:
os.makedirs(log_dir, exist_ok=True)
except Exception as e:
logger.error("Error creating API log directory %s: %s", log_dir, str(e))
# Fallback to base temp directory if sub-directory creation fails
return base_temp_dir
return log_dir
def _sanitize_filename_component(name: str) -> str:
if not name:
return "log"
sanitized = re.sub(r"[^A-Za-z0-9._-]+", "_", name) # Replace disallowed characters with underscore
sanitized = sanitized.strip(" ._") # Windows: trailing dots or spaces are not allowed
if not sanitized:
sanitized = "log"
return sanitized
def _short_hash(*parts: str, length: int = 10) -> str:
return hashlib.sha1(("|".join(parts)).encode("utf-8")).hexdigest()[:length]
def _build_log_filepath(log_dir: str, operation_id: str, request_url: str) -> str:
"""Build log filepath. We keep it well under common path length limits aiming for <= 240 characters total."""
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
slug = _sanitize_filename_component(operation_id) # Best-effort human-readable slug from operation_id
h = _short_hash(operation_id or "", request_url or "") # Short hash ties log to the full operation and URL
# Compute how much room we have for the slug given the directory length
# Keep total path length reasonably below ~260 on Windows.
max_total_path = 240
prefix = f"{timestamp}_"
suffix = f"_{h}.log"
if not slug:
slug = "op"
max_filename_len = max(60, max_total_path - len(log_dir) - 1)
max_slug_len = max(8, max_filename_len - len(prefix) - len(suffix))
if len(slug) > max_slug_len:
slug = slug[:max_slug_len].rstrip(" ._-")
return os.path.join(log_dir, f"{prefix}{slug}{suffix}")
def _format_data_for_logging(data: Any) -> str:
"""Helper to format data (dict, str, bytes) for logging."""
if isinstance(data, bytes):
try:
return data.decode("utf-8") # Try to decode as text
except UnicodeDecodeError:
return f"[Binary data of length {len(data)} bytes]"
elif isinstance(data, (dict, list)):
try:
return json.dumps(data, indent=2, ensure_ascii=False)
except TypeError:
return str(data) # Fallback for non-serializable objects
return str(data)
def log_request_response(
operation_id: str,
request_method: str,
request_url: str,
request_headers: dict | None = None,
request_params: dict | None = None,
request_data: Any = None,
response_status_code: int | None = None,
response_headers: dict | None = None,
response_content: Any = None,
error_message: str | None = None,
):
"""
Logs API request and response details to a file in the temp/api_logs directory.
Filenames are sanitized and length-limited for cross-platform safety.
If we still fail to write, we fall back to appending into api.log.
"""
try:
log_dir = get_log_directory()
filepath = _build_log_filepath(log_dir, operation_id, request_url)
log_content: list[str] = []
log_content.append(f"Timestamp: {datetime.datetime.now().isoformat()}")
log_content.append(f"Operation ID: {operation_id}")
log_content.append("-" * 30 + " REQUEST " + "-" * 30)
log_content.append(f"Method: {request_method}")
log_content.append(f"URL: {request_url}")
if request_headers:
log_content.append(f"Headers:\n{_format_data_for_logging(request_headers)}")
if request_params:
log_content.append(f"Params:\n{_format_data_for_logging(request_params)}")
if request_data is not None:
log_content.append(f"Data/Body:\n{_format_data_for_logging(request_data)}")
log_content.append("\n" + "-" * 30 + " RESPONSE " + "-" * 30)
if response_status_code is not None:
log_content.append(f"Status Code: {response_status_code}")
if response_headers:
log_content.append(f"Headers:\n{_format_data_for_logging(response_headers)}")
if response_content is not None:
log_content.append(f"Content:\n{_format_data_for_logging(response_content)}")
if error_message:
log_content.append(f"Error:\n{error_message}")
try:
with open(filepath, "w", encoding="utf-8") as f:
f.write("\n".join(log_content))
logger.debug("API log saved to: %s", filepath)
except Exception as e:
logger.error("Error writing API log to %s: %s", filepath, str(e))
except Exception as _log_e:
logging.debug("[DEBUG] log_request_response failed: %s", _log_e)
if __name__ == '__main__':
# Example usage (for testing the logger directly)
logger.setLevel(logging.DEBUG)
# Mock folder_paths for direct execution if not running within ComfyUI full context
if not hasattr(folder_paths, 'get_temp_directory'):
class MockFolderPaths:
def get_temp_directory(self):
# Create a local temp dir for testing if needed
p = os.path.join(os.path.dirname(__file__), 'temp_test_logs')
os.makedirs(p, exist_ok=True)
return p
folder_paths = MockFolderPaths()
log_request_response(
operation_id="test_operation_get",
request_method="GET",
request_url="https://api.example.com/test",
request_headers={"Authorization": "Bearer testtoken"},
request_params={"param1": "value1"},
response_status_code=200,
response_content={"message": "Success!"}
)
log_request_response(
operation_id="test_operation_post_error",
request_method="POST",
request_url="https://api.example.com/submit",
request_data={"key": "value", "nested": {"num": 123}},
error_message="Connection timed out"
)
log_request_response(
operation_id="test_binary_response",
request_method="GET",
request_url="https://api.example.com/image.png",
response_status_code=200,
response_content=b'\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR...' # Sample binary data
)
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