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from argparse import ArgumentParser
from logging import getLogger
from pathlib import Path
import yaml
from characters import get_character
from pipeline import SingingDialoguePipeline
logger = getLogger(__name__)
def get_parser():
parser = ArgumentParser()
parser.add_argument("--query_audios", nargs="+", type=Path, required=True)
parser.add_argument(
"--config_path", type=Path, default="config/cli/yaoyin_default.yaml"
)
parser.add_argument("--output_audio_folder", type=Path, required=True)
parser.add_argument("--eval_results_csv", type=Path, default=None)
return parser
def load_config(config_path: Path):
with open(config_path, "r") as f:
config = yaml.safe_load(f)
return config
def main():
parser = get_parser()
args = parser.parse_args()
config = load_config(args.config_path)
pipeline = SingingDialoguePipeline(config)
speaker = config["speaker"]
language = config["language"]
character_name = config["prompt_template_character"]
character = get_character(character_name)
prompt_template = character.prompt
args.output_audio_folder.mkdir(parents=True, exist_ok=True)
if config.get("evaluators", {}):
if args.eval_results_csv:
args.eval_results_csv.parent.mkdir(parents=True, exist_ok=True)
with open(args.eval_results_csv, "a") as f:
f.write(
f"query_audio,asr_model,llm_model,svs_model,melody_source,language,speaker,output_audio,asr_text,llm_text,metrics\n"
)
else:
logger.warning("No eval_results_csv provided, skipping evaluation")
try:
for query_audio in args.query_audios:
output_audio = args.output_audio_folder / f"{query_audio.stem}_response.wav"
results = pipeline.run(
query_audio,
language,
prompt_template,
speaker,
output_audio_path=output_audio,
)
if args.eval_results_csv and config.get("evaluators", {}):
metrics = pipeline.evaluate(output_audio, **results)
metrics.update(results.get("metrics", {}))
metrics_str = ",".join([f"{metrics[k]}" for k in sorted(metrics.keys())])
logger.info(
f"Input: {query_audio}, Output: {output_audio}, ASR results: {results['asr_text']}, LLM results: {results['llm_text']}"
)
with open(args.eval_results_csv, "a") as f:
f.write(
f"{query_audio},{config['asr_model']},{config['llm_model']},{config['svs_model']},{config['melody_source']},{config['language']},{config['speaker']},{output_audio},{results['asr_text']},{results['llm_text']},{metrics_str}\n"
)
except Exception as e:
import traceback
logger.error(traceback.format_exc())
raise e
if __name__ == "__main__":
main()
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