mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2026-04-19 22:09:10 +00:00
656 lines
34 KiB
Python
656 lines
34 KiB
Python
"""
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Internationalization (i18n) module for kt-cli.
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Supports English and Chinese languages, with automatic detection based on
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system locale or KT_LANG environment variable.
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"""
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import os
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from typing import Any
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# Message definitions for all supported languages
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MESSAGES: dict[str, dict[str, str]] = {
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"en": {
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# General
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"welcome": "Welcome to KTransformers!",
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"goodbye": "Goodbye!",
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"error": "Error",
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"warning": "Warning",
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"success": "Success",
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"info": "Info",
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"yes": "Yes",
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"no": "No",
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"cancel": "Cancel",
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"confirm": "Confirm",
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"done": "Done",
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"failed": "Failed",
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"skip": "Skip",
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"back": "Back",
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"next": "Next",
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"retry": "Retry",
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"abort": "Abort",
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# Version command
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"version_info": "KTransformers CLI",
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"version_python": "Python",
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"version_platform": "Platform",
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"version_cuda": "CUDA",
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"version_cuda_not_found": "Not found",
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"version_kt_kernel": "kt-kernel",
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"version_ktransformers": "ktransformers",
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"version_sglang": "sglang",
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"version_llamafactory": "llamafactory",
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"version_not_installed": "Not installed",
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# Install command
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"install_detecting_env": "Detecting environment managers...",
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"install_found": "Found {name} (version {version})",
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"install_not_found": "Not found: {name}",
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"install_checking_env": "Checking existing environments...",
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"install_env_exists": "Found existing 'kt' environment",
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"install_env_not_exists": "No 'kt' environment found",
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"install_no_env_manager": "No virtual environment manager detected",
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"install_select_method": "Please select installation method:",
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"install_method_conda": "Create new conda environment 'kt' (Recommended)",
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"install_method_venv": "Create new venv environment",
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"install_method_uv": "Create new uv environment (Fast)",
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"install_method_docker": "Use Docker container",
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"install_method_system": "Install to system Python (Not recommended)",
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"install_select_mode": "Please select installation mode:",
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"install_mode_inference": "Inference - Install kt-kernel + SGLang",
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"install_mode_sft": "Training - Install kt-sft + LlamaFactory",
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"install_mode_full": "Full - Install all components",
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"install_creating_env": "Creating {type} environment '{name}'...",
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"install_env_created": "Environment created successfully",
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"install_installing_deps": "Installing dependencies...",
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"install_checking_deps": "Checking dependency versions...",
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"install_dep_ok": "OK",
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"install_dep_outdated": "Needs update",
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"install_dep_missing": "Missing",
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"install_installing_pytorch": "Installing PyTorch...",
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"install_installing_from_requirements": "Installing from requirements file...",
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"install_deps_outdated": "Found {count} package(s) that need updating. Continue?",
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"install_updating": "Updating packages...",
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"install_complete": "Installation complete!",
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"install_activate_hint": "Activate environment: {command}",
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"install_start_hint": "Get started: kt run --help",
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"install_docker_pulling": "Pulling Docker image...",
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"install_docker_complete": "Docker image ready!",
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"install_docker_run_hint": "Run with: docker run --gpus all -p 30000:30000 {image} kt run {model}",
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"install_in_venv": "Running in virtual environment: {name}",
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"install_continue_without_venv": "Continue installing to system Python?",
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"install_already_installed": "All dependencies are already installed!",
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"install_confirm": "Install {count} package(s)?",
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# Install - System dependencies
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"install_checking_system_deps": "Checking system dependencies...",
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"install_dep_name": "Dependency",
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"install_dep_status": "Status",
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"install_deps_all_installed": "All system dependencies are installed",
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"install_deps_install_prompt": "Install missing dependencies?",
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"install_installing_system_deps": "Installing system dependencies...",
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"install_installing_dep": "Installing {name}",
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"install_dep_no_install_cmd": "No install command available for {name} on {os}",
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"install_dep_install_failed": "Failed to install {name}",
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"install_deps_skipped": "Skipping dependency installation",
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"install_deps_failed": "Failed to install system dependencies",
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# Install - CPU detection
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"install_auto_detect_cpu": "Auto-detecting CPU capabilities...",
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"install_cpu_features": "Detected CPU features: {features}",
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"install_cpu_no_features": "No advanced CPU features detected",
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# Install - Build configuration
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"install_build_config": "Build Configuration:",
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"install_native_warning": "Note: Binary optimized for THIS CPU only (not portable)",
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"install_building_from_source": "Building kt-kernel from source...",
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"install_build_failed": "Build failed",
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"install_build_success": "Build completed successfully",
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# Install - Verification
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"install_verifying": "Verifying installation...",
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"install_verify_success": "kt-kernel {version} ({variant} variant) installed successfully",
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"install_verify_failed": "Verification failed: {error}",
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# Install - Docker
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"install_docker_guide_title": "Docker Installation",
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"install_docker_guide_desc": "For Docker installation, please refer to the official guide:",
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# Config command
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"config_show_title": "Current Configuration",
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"config_set_success": "Configuration updated: {key} = {value}",
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"config_get_value": "{key} = {value}",
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"config_get_not_found": "Configuration key '{key}' not found",
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"config_reset_confirm": "This will reset all configurations to default. Continue?",
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"config_reset_success": "Configuration reset to default",
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"config_file_location": "Configuration file: {path}",
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# Doctor command
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"doctor_title": "KTransformers Environment Diagnostics",
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"doctor_checking": "Running diagnostics...",
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"doctor_check_python": "Python version",
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"doctor_check_cuda": "CUDA availability",
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"doctor_check_gpu": "GPU detection",
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"doctor_check_cpu": "CPU",
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"doctor_check_cpu_isa": "CPU Instructions",
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"doctor_check_numa": "NUMA Topology",
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"doctor_check_memory": "System memory",
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"doctor_check_disk": "Disk space",
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"doctor_check_packages": "Required packages",
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"doctor_check_env": "Environment variables",
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"doctor_status_ok": "OK",
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"doctor_status_warning": "Warning",
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"doctor_status_error": "Error",
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"doctor_gpu_found": "Found {count} GPU(s): {names}",
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"doctor_gpu_not_found": "No GPU detected",
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"doctor_cpu_info": "{name} ({cores} cores / {threads} threads)",
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"doctor_cpu_isa_info": "{isa_list}",
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"doctor_cpu_isa_missing": "Missing recommended: {missing}",
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"doctor_numa_info": "{nodes} node(s)",
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"doctor_numa_detail": "{node}: CPUs {cpus}",
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"doctor_memory_info": "{available} available / {total} total",
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"doctor_memory_freq": "{available} available / {total} total ({freq}MHz {type})",
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"doctor_disk_info": "{available} available at {path}",
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"doctor_all_ok": "All checks passed! Your environment is ready.",
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"doctor_has_issues": "Some issues were found. Please review the warnings/errors above.",
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# Run command
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"run_detecting_hardware": "Detecting hardware configuration...",
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"run_gpu_info": "GPU: {name} ({vram}GB VRAM)",
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"run_cpu_info": "CPU: {name} ({cores} cores, {numa} NUMA nodes)",
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"run_ram_info": "RAM: {total}GB",
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"run_checking_model": "Checking model status...",
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"run_model_path": "Model path: {path}",
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"run_weights_not_found": "Quantized weights not found",
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"run_quant_prompt": "Quantize model now? (This may take a while)",
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"run_quantizing": "Quantizing model...",
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"run_starting_server": "Starting server...",
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"run_server_mode": "Mode: SGLang + kt-kernel",
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"run_server_port": "Port: {port}",
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"run_gpu_experts": "GPU experts: {count}/layer",
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"run_cpu_threads": "CPU threads: {count}",
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"run_server_started": "Server started!",
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"run_api_url": "API URL: http://{host}:{port}",
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"run_docs_url": "Docs URL: http://{host}:{port}/docs",
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"run_stop_hint": "Press Ctrl+C to stop the server",
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"run_model_not_found": "Model '{name}' not found. Run 'kt download' first.",
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"run_multiple_matches": "Multiple models found. Please select:",
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"run_select_model": "Select model",
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"run_select_model_title": "Select a model to run",
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"run_select_model_prompt": "Enter number",
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"run_local_models": "Local Models (Downloaded)",
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"run_registered_models": "Registered Models",
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# Download command
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"download_list_title": "Available Models",
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"download_searching": "Searching for model '{name}'...",
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"download_found": "Found: {name}",
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"download_multiple_found": "Multiple matches found:",
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"download_select": "Select model to download:",
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"download_destination": "Destination: {path}",
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"download_starting": "Starting download...",
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"download_progress": "Downloading {name}...",
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"download_complete": "Download complete!",
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"download_already_exists": "Model already exists at {path}",
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"download_overwrite_prompt": "Overwrite existing files?",
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# Quant command
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"quant_input_path": "Input path: {path}",
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"quant_output_path": "Output path: {path}",
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"quant_method": "Quantization method: {method}",
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"quant_starting": "Starting quantization...",
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"quant_progress": "Quantizing...",
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"quant_complete": "Quantization complete!",
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"quant_input_not_found": "Input model not found at {path}",
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# SFT command
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"sft_mode_train": "Training mode",
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"sft_mode_chat": "Chat mode",
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"sft_mode_export": "Export mode",
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"sft_config_path": "Config file: {path}",
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"sft_starting": "Starting {mode}...",
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"sft_complete": "{mode} complete!",
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"sft_config_not_found": "Config file not found: {path}",
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# Bench command
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"bench_starting": "Starting benchmark...",
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"bench_type": "Benchmark type: {type}",
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"bench_complete": "Benchmark complete!",
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"bench_results_title": "Benchmark Results",
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# Common prompts
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"prompt_continue": "Continue?",
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"prompt_select": "Please select:",
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"prompt_enter_value": "Enter value:",
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"prompt_confirm_action": "Confirm this action?",
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# First-run setup - Model path selection
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"setup_model_path_title": "Model Storage Location",
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"setup_model_path_desc": "LLM models are large (50-200GB+). Please select a storage location with sufficient space:",
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"setup_scanning_disks": "Scanning available storage locations...",
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"setup_disk_option": "{path} ({available} available / {total} total)",
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"setup_disk_option_recommended": "{path} ({available} available / {total} total) [Recommended]",
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"setup_custom_path": "Enter custom path",
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"setup_enter_custom_path": "Enter the path for model storage",
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"setup_path_not_exist": "Path does not exist. Create it?",
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"setup_path_no_write": "No write permission for this path. Please choose another.",
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"setup_path_low_space": "Warning: Less than 100GB available. Large models may not fit.",
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"setup_model_path_set": "Model storage path set to: {path}",
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"setup_no_large_disk": "No large storage locations found. Using default path.",
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"setup_scanning_models": "Scanning for existing models...",
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"setup_found_models": "Found {count} model(s):",
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"setup_model_info": "{name} ({size}, {type})",
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"setup_no_models_found": "No existing models found in this location.",
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"setup_location_has_models": "{count} model(s) found",
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"setup_installing_completion": "Installing shell completion for {shell}...",
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"setup_completion_installed": "Shell completion installed! Restart terminal to enable.",
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"setup_completion_failed": "Failed to install shell completion. Run 'kt --install-completion' manually.",
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# Auto completion
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"completion_installed_title": "Tab Completion",
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"completion_installed_for": "Shell completion installed for {shell}",
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"completion_activate_now": "To enable completion in this terminal session, run:",
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"completion_next_session": "Completion will be automatically enabled in new terminal sessions.",
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# SGLang
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"sglang_not_found": "SGLang not found",
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"sglang_pypi_warning": "SGLang from PyPI may not be compatible with kt-kernel",
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"sglang_pypi_hint": 'SGLang from PyPI may not be compatible. Install from source: git clone https://github.com/kvcache-ai/sglang && cd sglang && pip install -e "python[all]"',
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"sglang_install_hint": 'Install SGLang: git clone https://github.com/kvcache-ai/sglang && cd sglang && pip install -e "python[all]"',
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"sglang_recommend_source": 'Recommend reinstalling from source: git clone https://github.com/kvcache-ai/sglang && cd sglang && pip install -e "python[all]"',
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"sglang_kt_kernel_not_supported": "SGLang does not support kt-kernel (missing --kt-gpu-prefill-token-threshold parameter)",
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"sglang_checking_kt_kernel_support": "Checking SGLang kt-kernel support...",
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"sglang_kt_kernel_supported": "SGLang kt-kernel support verified",
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# Chat
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"chat_proxy_detected": "Proxy detected in environment",
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"chat_proxy_confirm": "Use proxy for connection?",
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"chat_proxy_disabled": "Proxy disabled for this session",
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# Model command
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"model_supported_title": "KTransformers Supported Models",
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"model_column_model": "Model",
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"model_column_status": "Status",
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"model_column_local_path": "Local Path",
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"model_status_local": "Local",
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"model_status_not_downloaded": "Not downloaded",
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"model_usage_title": "Usage",
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"model_usage_download": "Download a model:",
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"model_usage_list_local": "List local models:",
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"model_usage_search": "Search models:",
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"model_storage_paths_title": "Model Storage Paths",
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"model_local_models_title": "Locally Downloaded Models",
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"model_available_models_title": "Available Models",
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"model_no_local_models": "No locally downloaded models found",
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"model_download_hint": "Download a model with:",
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"model_download_usage_hint": "Usage: kt model download <model-name>",
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"model_download_list_hint": "Use 'kt model download --list' to see available models.",
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"model_download_hf_hint": "Or specify a HuggingFace repo directly: kt model download org/model-name",
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"model_saved_to": "Model saved to: {path}",
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"model_start_with": "Start with: kt run {name}",
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"model_download_failed": "Download failed: {error}",
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"model_hf_cli_not_found": "huggingface-cli not found. Install with: pip install huggingface-hub",
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"model_path_not_exist": "Path does not exist: {path}",
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"model_create_directory": "Create directory {path}?",
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"model_created_directory": "Created directory: {path}",
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"model_create_dir_failed": "Failed to create directory: {error}",
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"model_path_added": "Added model path: {path}",
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"model_path_removed": "Removed model path: {path}",
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"model_path_not_found": "Path not found in configuration or cannot remove last path: {path}",
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"model_search_no_results": "No models found matching '{query}'",
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"model_search_results_title": "Search Results for '{query}'",
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"model_column_name": "Name",
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"model_column_hf_repo": "HuggingFace Repo",
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"model_column_aliases": "Aliases",
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# Coming soon
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"feature_coming_soon": "This feature is coming soon...",
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},
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"zh": {
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# General
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"welcome": "欢迎使用 KTransformers！",
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"goodbye": "再见！",
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"error": "错误",
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"warning": "警告",
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"success": "成功",
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"info": "信息",
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"yes": "是",
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"no": "否",
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"cancel": "取消",
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"confirm": "确认",
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"done": "完成",
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"failed": "失败",
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"skip": "跳过",
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"back": "返回",
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"next": "下一步",
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"retry": "重试",
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"abort": "中止",
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# Version command
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"version_info": "KTransformers CLI",
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"version_python": "Python",
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"version_platform": "平台",
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"version_cuda": "CUDA",
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"version_cuda_not_found": "未找到",
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"version_kt_kernel": "kt-kernel",
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"version_ktransformers": "ktransformers",
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"version_sglang": "sglang",
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"version_llamafactory": "llamafactory",
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"version_not_installed": "未安装",
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# Install command
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"install_detecting_env": "检测环境管理工具...",
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"install_found": "发现 {name} (版本 {version})",
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"install_not_found": "未找到: {name}",
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"install_checking_env": "检查现有环境...",
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"install_env_exists": "发现现有 'kt' 环境",
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"install_env_not_exists": "未发现 'kt' 环境",
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"install_no_env_manager": "未检测到虚拟环境管理工具",
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"install_select_method": "请选择安装方式:",
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"install_method_conda": "创建新的 conda 环境 'kt' (推荐)",
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"install_method_venv": "创建新的 venv 环境",
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"install_method_uv": "创建新的 uv 环境 (快速)",
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"install_method_docker": "使用 Docker 容器",
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"install_method_system": "安装到系统 Python (不推荐)",
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"install_select_mode": "请选择安装模式:",
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"install_mode_inference": "推理模式 - 安装 kt-kernel + SGLang",
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"install_mode_sft": "训练模式 - 安装 kt-sft + LlamaFactory",
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"install_mode_full": "完整安装 - 安装所有组件",
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"install_creating_env": "正在创建 {type} 环境 '{name}'...",
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"install_env_created": "环境创建成功",
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"install_installing_deps": "正在安装依赖...",
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"install_checking_deps": "检查依赖版本...",
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"install_dep_ok": "正常",
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"install_dep_outdated": "需更新",
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"install_dep_missing": "缺失",
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"install_installing_pytorch": "正在安装 PyTorch...",
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"install_installing_from_requirements": "从依赖文件安装...",
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"install_deps_outdated": "发现 {count} 个包需要更新，是否继续？",
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"install_updating": "正在更新包...",
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"install_complete": "安装完成！",
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"install_activate_hint": "激活环境: {command}",
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"install_start_hint": "开始使用: kt run --help",
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"install_docker_pulling": "正在拉取 Docker 镜像...",
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"install_docker_complete": "Docker 镜像已就绪！",
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"install_docker_run_hint": "运行: docker run --gpus all -p 30000:30000 {image} kt run {model}",
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"install_in_venv": "当前在虚拟环境中: {name}",
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"install_continue_without_venv": "继续安装到系统 Python？",
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"install_already_installed": "所有依赖已安装！",
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"install_confirm": "安装 {count} 个包？",
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# Install - System dependencies
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"install_checking_system_deps": "检查系统依赖...",
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"install_dep_name": "依赖项",
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"install_dep_status": "状态",
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"install_deps_all_installed": "所有系统依赖已安装",
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"install_deps_install_prompt": "是否安装缺失的依赖？",
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"install_installing_system_deps": "正在安装系统依赖...",
|
||
"install_installing_dep": "正在安装 {name}",
|
||
"install_dep_no_install_cmd": "{os} 系统上没有 {name} 的安装命令",
|
||
"install_dep_install_failed": "安装 {name} 失败",
|
||
"install_deps_skipped": "跳过依赖安装",
|
||
"install_deps_failed": "系统依赖安装失败",
|
||
# Install - CPU detection
|
||
"install_auto_detect_cpu": "正在自动检测 CPU 能力...",
|
||
"install_cpu_features": "检测到的 CPU 特性: {features}",
|
||
"install_cpu_no_features": "未检测到高级 CPU 特性",
|
||
# Install - Build configuration
|
||
"install_build_config": "构建配置:",
|
||
"install_native_warning": "注意: 二进制文件仅针对当前 CPU 优化（不可移植）",
|
||
"install_building_from_source": "正在从源码构建 kt-kernel...",
|
||
"install_build_failed": "构建失败",
|
||
"install_build_success": "构建成功",
|
||
# Install - Verification
|
||
"install_verifying": "正在验证安装...",
|
||
"install_verify_success": "kt-kernel {version} ({variant} 变体) 安装成功",
|
||
"install_verify_failed": "验证失败: {error}",
|
||
# Install - Docker
|
||
"install_docker_guide_title": "Docker 安装",
|
||
"install_docker_guide_desc": "有关 Docker 安装，请参阅官方指南:",
|
||
# Config command
|
||
"config_show_title": "当前配置",
|
||
"config_set_success": "配置已更新: {key} = {value}",
|
||
"config_get_value": "{key} = {value}",
|
||
"config_get_not_found": "未找到配置项 '{key}'",
|
||
"config_reset_confirm": "这将重置所有配置为默认值。是否继续？",
|
||
"config_reset_success": "配置已重置为默认值",
|
||
"config_file_location": "配置文件: {path}",
|
||
# Doctor command
|
||
"doctor_title": "KTransformers 环境诊断",
|
||
"doctor_checking": "正在运行诊断...",
|
||
"doctor_check_python": "Python 版本",
|
||
"doctor_check_cuda": "CUDA 可用性",
|
||
"doctor_check_gpu": "GPU 检测",
|
||
"doctor_check_cpu": "CPU",
|
||
"doctor_check_cpu_isa": "CPU 指令集",
|
||
"doctor_check_numa": "NUMA 拓扑",
|
||
"doctor_check_memory": "系统内存",
|
||
"doctor_check_disk": "磁盘空间",
|
||
"doctor_check_packages": "必需的包",
|
||
"doctor_check_env": "环境变量",
|
||
"doctor_status_ok": "正常",
|
||
"doctor_status_warning": "警告",
|
||
"doctor_status_error": "错误",
|
||
"doctor_gpu_found": "发现 {count} 个 GPU: {names}",
|
||
"doctor_gpu_not_found": "未检测到 GPU",
|
||
"doctor_cpu_info": "{name} ({cores} 核心 / {threads} 线程)",
|
||
"doctor_cpu_isa_info": "{isa_list}",
|
||
"doctor_cpu_isa_missing": "缺少推荐指令集: {missing}",
|
||
"doctor_numa_info": "{nodes} 个节点",
|
||
"doctor_numa_detail": "{node}: CPU {cpus}",
|
||
"doctor_memory_info": "{available} 可用 / {total} 总计",
|
||
"doctor_memory_freq": "{available} 可用 / {total} 总计 ({freq}MHz {type})",
|
||
"doctor_disk_info": "{path} 有 {available} 可用空间",
|
||
"doctor_all_ok": "所有检查通过！您的环境已就绪。",
|
||
"doctor_has_issues": "发现一些问题，请查看上方的警告/错误信息。",
|
||
# Run command
|
||
"run_detecting_hardware": "检测硬件配置...",
|
||
"run_gpu_info": "GPU: {name} ({vram}GB 显存)",
|
||
"run_cpu_info": "CPU: {name} ({cores} 核心, {numa} NUMA 节点)",
|
||
"run_ram_info": "内存: {total}GB",
|
||
"run_checking_model": "检查模型状态...",
|
||
"run_model_path": "模型路径: {path}",
|
||
"run_weights_not_found": "未找到量化权重",
|
||
"run_quant_prompt": "是否现在量化模型？(这可能需要一些时间)",
|
||
"run_quantizing": "正在量化模型...",
|
||
"run_starting_server": "正在启动服务器...",
|
||
"run_server_mode": "模式: SGLang + kt-kernel",
|
||
"run_server_port": "端口: {port}",
|
||
"run_gpu_experts": "GPU 专家: {count}/层",
|
||
"run_cpu_threads": "CPU 线程: {count}",
|
||
"run_server_started": "服务器已启动！",
|
||
"run_api_url": "API 地址: http://{host}:{port}",
|
||
"run_docs_url": "文档地址: http://{host}:{port}/docs",
|
||
"run_stop_hint": "按 Ctrl+C 停止服务器",
|
||
"run_model_not_found": "未找到模型 '{name}'。请先运行 'kt download'。",
|
||
"run_multiple_matches": "找到多个匹配的模型，请选择:",
|
||
"run_select_model": "选择模型",
|
||
"run_select_model_title": "选择要运行的模型",
|
||
"run_select_model_prompt": "输入编号",
|
||
"run_local_models": "本地模型 (已下载)",
|
||
"run_registered_models": "注册模型",
|
||
# Download command
|
||
"download_list_title": "可用模型",
|
||
"download_searching": "正在搜索模型 '{name}'...",
|
||
"download_found": "找到: {name}",
|
||
"download_multiple_found": "找到多个匹配:",
|
||
"download_select": "选择要下载的模型:",
|
||
"download_destination": "目标路径: {path}",
|
||
"download_starting": "开始下载...",
|
||
"download_progress": "正在下载 {name}...",
|
||
"download_complete": "下载完成！",
|
||
"download_already_exists": "模型已存在于 {path}",
|
||
"download_overwrite_prompt": "是否覆盖现有文件？",
|
||
# Quant command
|
||
"quant_input_path": "输入路径: {path}",
|
||
"quant_output_path": "输出路径: {path}",
|
||
"quant_method": "量化方法: {method}",
|
||
"quant_starting": "开始量化...",
|
||
"quant_progress": "正在量化...",
|
||
"quant_complete": "量化完成！",
|
||
"quant_input_not_found": "未找到输入模型: {path}",
|
||
# SFT command
|
||
"sft_mode_train": "训练模式",
|
||
"sft_mode_chat": "聊天模式",
|
||
"sft_mode_export": "导出模式",
|
||
"sft_config_path": "配置文件: {path}",
|
||
"sft_starting": "正在启动 {mode}...",
|
||
"sft_complete": "{mode} 完成！",
|
||
"sft_config_not_found": "未找到配置文件: {path}",
|
||
# Bench command
|
||
"bench_starting": "开始基准测试...",
|
||
"bench_type": "测试类型: {type}",
|
||
"bench_complete": "基准测试完成！",
|
||
"bench_results_title": "基准测试结果",
|
||
# Common prompts
|
||
"prompt_continue": "是否继续？",
|
||
"prompt_select": "请选择:",
|
||
"prompt_enter_value": "请输入:",
|
||
"prompt_confirm_action": "确认此操作？",
|
||
# First-run setup - Model path selection
|
||
"setup_model_path_title": "模型存储位置",
|
||
"setup_model_path_desc": "大语言模型体积较大（50-200GB+）。请选择一个有足够空间的存储位置：",
|
||
"setup_scanning_disks": "正在扫描可用存储位置...",
|
||
"setup_disk_option": "{path} (可用 {available} / 总共 {total})",
|
||
"setup_disk_option_recommended": "{path} (可用 {available} / 总共 {total}) [推荐]",
|
||
"setup_custom_path": "输入自定义路径",
|
||
"setup_enter_custom_path": "请输入模型存储路径",
|
||
"setup_path_not_exist": "路径不存在，是否创建？",
|
||
"setup_path_no_write": "没有该路径的写入权限，请选择其他路径。",
|
||
"setup_path_low_space": "警告：可用空间不足 100GB，可能无法存储大型模型。",
|
||
"setup_model_path_set": "模型存储路径已设置为: {path}",
|
||
"setup_no_large_disk": "未发现大容量存储位置，使用默认路径。",
|
||
"setup_scanning_models": "正在扫描已有模型...",
|
||
"setup_found_models": "发现 {count} 个模型:",
|
||
"setup_model_info": "{name} ({size}, {type})",
|
||
"setup_no_models_found": "该位置未发现已有模型。",
|
||
"setup_location_has_models": "发现 {count} 个模型",
|
||
"setup_installing_completion": "正在为 {shell} 安装命令补全...",
|
||
"setup_completion_installed": "命令补全已安装！重启终端后生效。",
|
||
"setup_completion_failed": "命令补全安装失败。请手动运行 'kt --install-completion'。",
|
||
# Auto completion
|
||
"completion_installed_title": "命令补全",
|
||
"completion_installed_for": "已为 {shell} 安装命令补全",
|
||
"completion_activate_now": "在当前终端会话中启用补全，请运行：",
|
||
"completion_next_session": "新的终端会话将自动启用补全。",
|
||
# SGLang
|
||
"sglang_not_found": "未找到 SGLang",
|
||
"sglang_pypi_warning": "PyPI 版本的 SGLang 可能与 kt-kernel 不兼容",
|
||
"sglang_pypi_hint": 'PyPI 版本可能不兼容。从源码安装: git clone https://github.com/kvcache-ai/sglang && cd sglang && pip install -e "python[all]"',
|
||
"sglang_install_hint": '安装 SGLang: git clone https://github.com/kvcache-ai/sglang && cd sglang && pip install -e "python[all]"',
|
||
"sglang_recommend_source": '建议从源码重新安装: git clone https://github.com/kvcache-ai/sglang && cd sglang && pip install -e "python[all]"',
|
||
"sglang_kt_kernel_not_supported": "SGLang 不支持 kt-kernel (缺少 --kt-gpu-prefill-token-threshold 参数)",
|
||
"sglang_checking_kt_kernel_support": "正在检查 SGLang kt-kernel 支持...",
|
||
"sglang_kt_kernel_supported": "SGLang kt-kernel 支持已验证",
|
||
# Chat
|
||
"chat_proxy_detected": "检测到环境中存在代理设置",
|
||
"chat_proxy_confirm": "是否使用代理连接？",
|
||
"chat_proxy_disabled": "已在本次会话中禁用代理",
|
||
# Model command
|
||
"model_supported_title": "KTransformers 支持的模型",
|
||
"model_column_model": "模型",
|
||
"model_column_status": "状态",
|
||
"model_column_local_path": "本地路径",
|
||
"model_status_local": "本地",
|
||
"model_status_not_downloaded": "未下载",
|
||
"model_usage_title": "使用方法",
|
||
"model_usage_download": "下载模型:",
|
||
"model_usage_list_local": "列出本地模型:",
|
||
"model_usage_search": "搜索模型:",
|
||
"model_storage_paths_title": "模型存储路径",
|
||
"model_local_models_title": "本地已下载的模型",
|
||
"model_available_models_title": "可用模型",
|
||
"model_no_local_models": "未找到本地已下载的模型",
|
||
"model_download_hint": "下载模型:",
|
||
"model_download_usage_hint": "用法: kt model download <模型名称>",
|
||
"model_download_list_hint": "使用 'kt model download --list' 查看可用模型。",
|
||
"model_download_hf_hint": "或直接指定 HuggingFace 仓库: kt model download org/model-name",
|
||
"model_saved_to": "模型已保存到: {path}",
|
||
"model_start_with": "启动命令: kt run {name}",
|
||
"model_download_failed": "下载失败: {error}",
|
||
"model_hf_cli_not_found": "未找到 huggingface-cli。请安装: pip install huggingface-hub",
|
||
"model_path_not_exist": "路径不存在: {path}",
|
||
"model_create_directory": "创建目录 {path}？",
|
||
"model_created_directory": "已创建目录: {path}",
|
||
"model_create_dir_failed": "创建目录失败: {error}",
|
||
"model_path_added": "已添加模型路径: {path}",
|
||
"model_path_removed": "已移除模型路径: {path}",
|
||
"model_path_not_found": "路径未找到或无法移除最后一个路径: {path}",
|
||
"model_search_no_results": "未找到匹配 '{query}' 的模型",
|
||
"model_search_results_title": "'{query}' 的搜索结果",
|
||
"model_column_name": "名称",
|
||
"model_column_hf_repo": "HuggingFace 仓库",
|
||
"model_column_aliases": "别名",
|
||
# Coming soon
|
||
"feature_coming_soon": "此功能即将推出...",
|
||
},
|
||
}
|
||
|
||
|
||
# Cache for language detection to avoid repeated I/O
|
||
_lang_cache: str | None = None
|
||
|
||
|
||
def get_lang() -> str:
|
||
"""
|
||
Detect the current language setting.
|
||
|
||
Priority:
|
||
1. KT_LANG environment variable
|
||
2. Config file general.language setting
|
||
3. LANG environment variable (if config is "auto")
|
||
4. Default to English
|
||
|
||
Returns:
|
||
Language code: "zh" for Chinese, "en" for English
|
||
"""
|
||
global _lang_cache
|
||
|
||
# 1. Check KT_LANG environment variable (highest priority)
|
||
kt_lang = os.environ.get("KT_LANG", "").lower()
|
||
if kt_lang:
|
||
return "zh" if kt_lang.startswith("zh") else "en"
|
||
|
||
# 2. Return cached value if available (avoids I/O on every call)
|
||
if _lang_cache is not None:
|
||
return _lang_cache
|
||
|
||
# 3. Check config file setting (with caching)
|
||
# Import here to avoid circular imports
|
||
from kt_kernel.cli.config.settings import get_settings
|
||
|
||
try:
|
||
settings = get_settings()
|
||
config_lang = settings.get("general.language", "auto")
|
||
if config_lang and config_lang != "auto":
|
||
lang = "zh" if config_lang.lower().startswith("zh") else "en"
|
||
_lang_cache = lang
|
||
return lang
|
||
except Exception:
|
||
# If settings fail to load, continue with system detection
|
||
pass
|
||
|
||
# 4. Check system LANG environment variable
|
||
system_lang = os.environ.get("LANG", "").lower()
|
||
lang = "zh" if system_lang.startswith("zh") else "en"
|
||
_lang_cache = lang
|
||
return lang
|
||
|
||
|
||
def t(msg_key: str, **kwargs: Any) -> str:
|
||
"""
|
||
Translate a message key to the current language.
|
||
|
||
Args:
|
||
msg_key: Message key to translate
|
||
**kwargs: Format arguments for the message
|
||
|
||
Returns:
|
||
Translated and formatted message string
|
||
|
||
Example:
|
||
>>> t("welcome")
|
||
"Welcome to KTransformers!" # or "欢迎使用 KTransformers！" in Chinese
|
||
|
||
>>> t("install_found", name="conda", version="24.1.0")
|
||
"Found conda (version 24.1.0)"
|
||
"""
|
||
lang = get_lang()
|
||
messages = MESSAGES.get(lang, MESSAGES["en"])
|
||
message = messages.get(msg_key, MESSAGES["en"].get(msg_key, msg_key))
|
||
|
||
if kwargs:
|
||
try:
|
||
return message.format(**kwargs)
|
||
except KeyError:
|
||
return message
|
||
return message
|
||
|
||
|
||
def set_lang(lang: str) -> None:
|
||
"""
|
||
Set the language for the current session.
|
||
|
||
Args:
|
||
lang: Language code ("en" or "zh")
|
||
"""
|
||
global _lang_cache
|
||
os.environ["KT_LANG"] = lang
|
||
_lang_cache = lang # Update cache when language is explicitly set
|