Merge pull request #161 from s3ldc/cli-arg-validation
Improve CLI argument validation and help text
This commit is contained in:
xliucs
@ -3,30 +3,22 @@
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VoxCPM Command Line Interface
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Unified CLI for voice cloning, direct TTS synthesis, and batch processing.
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Usage examples:
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# Direct synthesis (single sample)
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voxcpm --text "Hello world" --output output.wav
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# Voice cloning (with reference audio and text)
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voxcpm --text "Hello world" --prompt-audio voice.wav --prompt-text "reference text" --output output.wav --denoise
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# Batch processing (each line in the file is one sample)
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voxcpm --input texts.txt --output-dir ./outputs/
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"""
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import argparse
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import os
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import sys
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from pathlib import Path
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from typing import Optional, List
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import soundfile as sf
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from voxcpm.core import VoxCPM
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# -----------------------------
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# Validators
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# -----------------------------
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def validate_file_exists(file_path: str, file_type: str = "file") -> Path:
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"""Validate that a file exists."""
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path = Path(file_path)
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if not path.exists():
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raise FileNotFoundError(f"{file_type} '{file_path}' does not exist")
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@ -34,47 +26,68 @@ def validate_file_exists(file_path: str, file_type: str = "file") -> Path:
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def validate_output_path(output_path: str) -> Path:
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"""Validate the output path and create parent directories if needed."""
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path = Path(output_path)
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path.parent.mkdir(parents=True, exist_ok=True)
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return path
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def load_model(args) -> VoxCPM:
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"""Load VoxCPM model.
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def validate_ranges(args, parser):
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"""Validate numeric argument ranges."""
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if not (0.1 <= args.cfg_value <= 10.0):
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parser.error("--cfg-value must be between 0.1 and 10.0")
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Prefer --model-path if provided; otherwise use from_pretrained (Hub).
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"""
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if not (1 <= args.inference_timesteps <= 100):
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parser.error("--inference-timesteps must be between 1 and 100")
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if args.lora_r <= 0:
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parser.error("--lora-r must be a positive integer")
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if args.lora_alpha <= 0:
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parser.error("--lora-alpha must be a positive integer")
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if not (0.0 <= args.lora_dropout <= 1.0):
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parser.error("--lora-dropout must be between 0.0 and 1.0")
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# -----------------------------
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# Model loading
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# -----------------------------
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def load_model(args) -> VoxCPM:
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print("Loading VoxCPM model...", file=sys.stderr)
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# 兼容旧参数：ZIPENHANCER_MODEL_PATH 环境变量作为默认
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zipenhancer_path = getattr(args, "zipenhancer_path", None) or os.environ.get(
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"ZIPENHANCER_MODEL_PATH", None
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)
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# Build LoRA config if lora_path is provided
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# Build LoRA config if provided
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lora_config = None
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lora_weights_path = getattr(args, "lora_path", None)
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if lora_weights_path:
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from voxcpm.model.voxcpm import LoRAConfig
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lora_config = LoRAConfig(
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enable_lm=getattr(args, "lora_enable_lm", True),
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enable_dit=getattr(args, "lora_enable_dit", True),
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enable_proj=getattr(args, "lora_enable_proj", False),
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r=getattr(args, "lora_r", 32),
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alpha=getattr(args, "lora_alpha", 16),
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dropout=getattr(args, "lora_dropout", 0.0),
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)
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print(f"LoRA config: r={lora_config.r}, alpha={lora_config.alpha}, "
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f"lm={lora_config.enable_lm}, dit={lora_config.enable_dit}, proj={lora_config.enable_proj}", file=sys.stderr)
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# Load from local path if provided
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if getattr(args, "model_path", None):
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lora_config = LoRAConfig(
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enable_lm=not args.lora_disable_lm,
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enable_dit=not args.lora_disable_dit,
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enable_proj=args.lora_enable_proj,
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r=args.lora_r,
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alpha=args.lora_alpha,
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dropout=args.lora_dropout,
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)
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print(
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f"LoRA config: r={lora_config.r}, alpha={lora_config.alpha}, "
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f"lm={lora_config.enable_lm}, dit={lora_config.enable_dit}, proj={lora_config.enable_proj}",
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file=sys.stderr,
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)
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# Load local model if specified
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if args.model_path:
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try:
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model = VoxCPM(
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voxcpm_model_path=args.model_path,
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zipenhancer_model_path=zipenhancer_path,
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enable_denoiser=not getattr(args, "no_denoiser", False),
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enable_denoiser=not args.no_denoiser,
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lora_config=lora_config,
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lora_weights_path=lora_weights_path,
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)
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@ -84,14 +97,14 @@ def load_model(args) -> VoxCPM:
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print(f"Failed to load model (local): {e}", file=sys.stderr)
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sys.exit(1)
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# Otherwise, try from_pretrained (Hub); exit on failure
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# Load from Hugging Face Hub
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try:
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model = VoxCPM.from_pretrained(
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hf_model_id=getattr(args, "hf_model_id", "openbmb/VoxCPM1.5"),
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load_denoiser=not getattr(args, "no_denoiser", False),
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hf_model_id=args.hf_model_id,
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load_denoiser=not args.no_denoiser,
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zipenhancer_model_id=zipenhancer_path,
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cache_dir=getattr(args, "cache_dir", None),
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local_files_only=getattr(args, "local_files_only", False),
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cache_dir=args.cache_dir,
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local_files_only=args.local_files_only,
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lora_config=lora_config,
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lora_weights_path=lora_weights_path,
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)
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@ -102,33 +115,22 @@ def load_model(args) -> VoxCPM:
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sys.exit(1)
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# -----------------------------
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# Commands
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# -----------------------------
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def cmd_clone(args):
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"""Voice cloning command."""
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# Validate inputs
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if not args.text:
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print("Error: Please provide text to synthesize (--text)", file=sys.stderr)
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sys.exit(1)
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sys.exit("Error: Please provide --text for synthesis")
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if not args.prompt_audio:
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print("Error: Voice cloning requires a reference audio (--prompt-audio)", file=sys.stderr)
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sys.exit(1)
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if not args.prompt_audio or not args.prompt_text:
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sys.exit("Error: Voice cloning requires both --prompt-audio and --prompt-text")
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if not args.prompt_text:
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print("Error: Voice cloning requires a reference text (--prompt-text)", file=sys.stderr)
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sys.exit(1)
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# Validate files
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prompt_audio_path = validate_file_exists(args.prompt_audio, "reference audio file")
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output_path = validate_output_path(args.output)
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# Load model
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model = load_model(args)
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# Generate audio
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print(f"Synthesizing text: {args.text}", file=sys.stderr)
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print(f"Reference audio: {prompt_audio_path}", file=sys.stderr)
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print(f"Reference text: {args.prompt_text}", file=sys.stderr)
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audio_array = model.generate(
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text=args.text,
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prompt_wav_path=str(prompt_audio_path),
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@ -136,30 +138,21 @@ def cmd_clone(args):
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cfg_value=args.cfg_value,
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inference_timesteps=args.inference_timesteps,
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normalize=args.normalize,
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denoise=args.denoise
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denoise=args.denoise,
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)
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# Save audio
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sf.write(str(output_path), audio_array, model.tts_model.sample_rate)
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print(f"Saved audio to: {output_path}", file=sys.stderr)
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# Stats
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duration = len(audio_array) / model.tts_model.sample_rate
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print(f"Duration: {duration:.2f}s", file=sys.stderr)
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print(f"Saved audio to: {output_path} ({duration:.2f}s)", file=sys.stderr)
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def cmd_synthesize(args):
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"""Direct TTS synthesis command."""
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# Validate inputs
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if not args.text:
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print("Error: Please provide text to synthesize (--text)", file=sys.stderr)
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sys.exit(1)
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# Validate output path
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sys.exit("Error: Please provide --text for synthesis")
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output_path = validate_output_path(args.output)
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# Load model
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model = load_model(args)
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# Generate audio
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print(f"Synthesizing text: {args.text}", file=sys.stderr)
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audio_array = model.generate(
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text=args.text,
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@ -168,45 +161,35 @@ def cmd_synthesize(args):
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cfg_value=args.cfg_value,
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inference_timesteps=args.inference_timesteps,
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normalize=args.normalize,
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denoise=False # 无参考音频时不需要降噪
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denoise=False,
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)
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# Save audio
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sf.write(str(output_path), audio_array, model.tts_model.sample_rate)
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print(f"Saved audio to: {output_path}", file=sys.stderr)
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# Stats
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duration = len(audio_array) / model.tts_model.sample_rate
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print(f"Duration: {duration:.2f}s", file=sys.stderr)
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print(f"Saved audio to: {output_path} ({duration:.2f}s)", file=sys.stderr)
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def cmd_batch(args):
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"""Batch synthesis command."""
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# Validate input file
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input_file = validate_file_exists(args.input, "input file")
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output_dir = Path(args.output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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try:
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with open(input_file, 'r', encoding='utf-8') as f:
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with open(input_file, "r", encoding="utf-8") as f:
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texts = [line.strip() for line in f if line.strip()]
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except Exception as e:
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print(f"Failed to read input file: {e}", file=sys.stderr)
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sys.exit(1)
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if not texts:
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print("Error: Input file is empty or contains no valid lines", file=sys.stderr)
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sys.exit(1)
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print(f"Found {len(texts)} lines to process", file=sys.stderr)
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sys.exit("Error: Input file is empty")
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model = load_model(args)
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prompt_audio_path = None
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if args.prompt_audio:
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prompt_audio_path = str(validate_file_exists(args.prompt_audio, "reference audio file"))
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success_count = 0
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for i, text in enumerate(texts, 1):
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print(f"\nProcessing {i}/{len(texts)}: {text[:50]}...", file=sys.stderr)
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for i, text in enumerate(texts, 1):
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try:
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audio_array = model.generate(
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text=text,
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@ -215,8 +198,9 @@ def cmd_batch(args):
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cfg_value=args.cfg_value,
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inference_timesteps=args.inference_timesteps,
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normalize=args.normalize,
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denoise=args.denoise and prompt_audio_path is not None
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denoise=args.denoise and prompt_audio_path is not None,
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)
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output_file = output_dir / f"output_{i:03d}.wav"
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sf.write(str(output_file), audio_array, model.tts_model.sample_rate)
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@ -225,102 +209,98 @@ def cmd_batch(args):
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success_count += 1
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except Exception as e:
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print(f" Failed: {e}", file=sys.stderr)
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continue
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print(f"Failed on line {i}: {e}", file=sys.stderr)
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print(f"\nBatch finished: {success_count}/{len(texts)} succeeded", file=sys.stderr)
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# -----------------------------
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# Parser
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# -----------------------------
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def _build_unified_parser():
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"""Build unified argument parser (no subcommands, route by args)."""
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parser = argparse.ArgumentParser(
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description="VoxCPM CLI (single parser) - voice cloning, direct TTS, and batch processing",
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description="VoxCPM CLI - voice cloning, direct TTS, and batch processing",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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# Direct synthesis (single sample)
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voxcpm --text "Hello world" --output out.wav
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# Voice cloning (reference audio + text)
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voxcpm --text "Hello world" --prompt-audio voice.wav --prompt-text "reference text" --output out.wav --denoise
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# Batch processing
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voxcpm --text "Hello" --prompt-audio ref.wav --prompt-text "hi" --output out.wav --denoise
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voxcpm --input texts.txt --output-dir ./outs
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# Select model (from Hub)
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voxcpm --text "Hello" --output out.wav --hf-model-id openbmb/VoxCPM-0.5B
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"""
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""",
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)
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# Task selection (automatic routing by presence of args)
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parser.add_argument("--input", "-i", help="Input text file (one line per sample)")
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parser.add_argument("--output-dir", "-od", help="Output directory (for batch mode)")
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parser.add_argument("--text", "-t", help="Text to synthesize (single-sample mode)")
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parser.add_argument("--output", "-o", help="Output audio file path (single-sample mode)")
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# Mode selection
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parser.add_argument("--input", "-i", help="Input text file (batch mode only)")
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parser.add_argument("--output-dir", "-od", help="Output directory (batch mode only)")
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parser.add_argument("--text", "-t", help="Text to synthesize (single or clone mode)")
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parser.add_argument("--output", "-o", help="Output audio file path (single or clone mode)")
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# Prompt audio (for voice cloning)
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parser.add_argument("--prompt-audio", "-pa", help="Reference audio file path")
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# Prompt
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parser.add_argument("--prompt-audio", "-pa", help="Reference audio file path (clone mode)")
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parser.add_argument("--prompt-text", "-pt", help="Reference text corresponding to the audio")
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parser.add_argument("--prompt-file", "-pf", help="Reference text file corresponding to the audio")
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parser.add_argument("--denoise", action="store_true", help="Enable prompt speech enhancement (denoising)")
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parser.add_argument("--denoise", action="store_true", help="Enable prompt speech enhancement")
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# Generation parameters
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parser.add_argument("--cfg-value", type=float, default=2.0, help="CFG guidance scale (default: 2.0)")
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parser.add_argument("--inference-timesteps", type=int, default=10, help="Inference steps (default: 10)")
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parser.add_argument("--cfg-value", type=float, default=2.0,
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help="CFG guidance scale (float, recommended 0.5–5.0, default: 2.0)")
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parser.add_argument("--inference-timesteps", type=int, default=10,
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help="Inference steps (int, 1–100, default: 10)")
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parser.add_argument("--normalize", action="store_true", help="Enable text normalization")
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# Model loading parameters
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parser.add_argument("--model-path", type=str, help="Local VoxCPM model path (overrides Hub download)")
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parser.add_argument("--hf-model-id", type=str, default="openbmb/VoxCPM1.5", help="Hugging Face repo id (e.g., openbmb/VoxCPM1.5 or openbmb/VoxCPM-0.5B)")
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# Model loading
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parser.add_argument("--model-path", type=str, help="Local VoxCPM model path")
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parser.add_argument("--hf-model-id", type=str, default="openbmb/VoxCPM1.5",
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help="Hugging Face repo id (default: openbmb/VoxCPM1.5)")
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parser.add_argument("--cache-dir", type=str, help="Cache directory for Hub downloads")
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parser.add_argument("--local-files-only", action="store_true", help="Use only local files (no network)")
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parser.add_argument("--local-files-only", action="store_true", help="Disable network access")
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parser.add_argument("--no-denoiser", action="store_true", help="Disable denoiser model loading")
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parser.add_argument("--zipenhancer-path", type=str, default="iic/speech_zipenhancer_ans_multiloss_16k_base", help="ZipEnhancer model id or local path (default reads from env)")
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parser.add_argument("--zipenhancer-path", type=str,
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help="ZipEnhancer model id or local path (or env ZIPENHANCER_MODEL_PATH)")
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# LoRA parameters
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parser.add_argument("--lora-path", type=str, help="Path to LoRA weights (.pth file or directory containing lora_weights.ckpt)")
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parser.add_argument("--lora-r", type=int, default=32, help="LoRA rank (default: 32)")
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parser.add_argument("--lora-alpha", type=int, default=16, help="LoRA alpha scaling factor (default: 16)")
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parser.add_argument("--lora-dropout", type=float, default=0.0, help="LoRA dropout rate (default: 0.0)")
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parser.add_argument("--lora-enable-lm", action="store_true", default=True, help="Apply LoRA to LM layers (default: True)")
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parser.add_argument("--lora-enable-dit", action="store_true", default=True, help="Apply LoRA to DiT layers (default: True)")
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parser.add_argument("--lora-enable-proj", action="store_true", default=False, help="Apply LoRA to projection layers (default: False)")
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# LoRA
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parser.add_argument("--lora-path", type=str, help="Path to LoRA weights")
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parser.add_argument("--lora-r", type=int, default=32, help="LoRA rank (positive int, default: 32)")
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parser.add_argument("--lora-alpha", type=int, default=16, help="LoRA alpha (positive int, default: 16)")
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parser.add_argument("--lora-dropout", type=float, default=0.0,
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help="LoRA dropout rate (0.0–1.0, default: 0.0)")
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parser.add_argument("--lora-disable-lm", action="store_true", help="Disable LoRA on LM layers")
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parser.add_argument("--lora-disable-dit", action="store_true", help="Disable LoRA on DiT layers")
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parser.add_argument("--lora-enable-proj", action="store_true", help="Enable LoRA on projection layers")
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return parser
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# -----------------------------
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# Entrypoint
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# -----------------------------
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def main():
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"""Unified CLI entrypoint: route by provided arguments."""
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parser = _build_unified_parser()
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args = parser.parse_args()
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# Routing: prefer batch → single (clone/direct)
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# Validate ranges
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validate_ranges(args, parser)
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# Mode conflict checks
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if args.input and args.text:
|
||||
parser.error("Use either batch mode (--input) or single mode (--text), not both.")
|
||||
|
||||
# Batch mode
|
||||
if args.input:
|
||||
if not args.output_dir:
|
||||
print("Error: Batch mode requires --output-dir", file=sys.stderr)
|
||||
parser.print_help()
|
||||
sys.exit(1)
|
||||
parser.error("Batch mode requires --output-dir")
|
||||
return cmd_batch(args)
|
||||
|
||||
# Single-sample mode
|
||||
# Single mode
|
||||
if not args.text or not args.output:
|
||||
print("Error: Single-sample mode requires --text and --output", file=sys.stderr)
|
||||
parser.print_help()
|
||||
sys.exit(1)
|
||||
parser.error("Single-sample mode requires --text and --output")
|
||||
|
||||
# If prompt audio+text provided → voice cloning
|
||||
# Clone mode
|
||||
if args.prompt_audio or args.prompt_text:
|
||||
if not args.prompt_text and args.prompt_file:
|
||||
assert os.path.isfile(args.prompt_file), "Prompt file does not exist or is not accessible."
|
||||
|
||||
with open(args.prompt_file, 'r', encoding='utf-8') as f:
|
||||
args.prompt_text = f.read()
|
||||
|
||||
if not args.prompt_audio or not args.prompt_text:
|
||||
print("Error: Voice cloning requires both --prompt-audio and --prompt-text", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
return cmd_clone(args)
|
||||
|
||||
# Otherwise → direct synthesis
|
||||
# Direct synthesis
|
||||
return cmd_synthesize(args)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user