import argparse

from experiment.const_pipeline_names import GOLD_TRANSCRIPT
from experiment.experiment_dependency_provider import get_record_provider, get_repository
from sziszapangma.core.transformer.web_embedding_transformer import WebEmbeddingTransformer
from sziszapangma.integration.experiment_manager import ExperimentManager
from sziszapangma.integration.task.classic_wer_metric_task import ClassicWerMetricTask
from sziszapangma.integration.task.embedding_wer_metrics_task import EmbeddingWerMetricsTask


def run_word_wer_pipeline(dataset_name: str, asr_name: str):
    record_provider = get_record_provider(dataset_name)
    experiment_processor = ExperimentManager(
        record_id_iterator=record_provider,
        processing_tasks=[
            ClassicWerMetricTask(
                task_name=f'ClassicWerMetricTask___{dataset_name}___{asr_name}',
                asr_property_name=f'{asr_name}__result',
                gold_transcript_property_name=GOLD_TRANSCRIPT,
                metrics_property_name=f'{asr_name}__word_wer_classic_metrics',
                require_update=False,
                alignment_property_name=f'{asr_name}__word_wer_classic_alignment'
            ),
            EmbeddingWerMetricsTask(
                task_name='EmbeddingWerMetricsTask',
                asr_property_name=f'{asr_name}__result',
                gold_transcript_property_name=GOLD_TRANSCRIPT,
                metrics_property_name=f'{asr_name}__word_wer_embeddings_metrics',
                require_update=False,
                embedding_transformer=WebEmbeddingTransformer('pl', 'http://localhost:5003', 'fjsd-mkwe-oius-m9h2'),
                alignment_property_name=f'{asr_name}__word_wer_embeddings_alignment'
            )
        ],
        experiment_repository=get_repository(dataset_name),
        relation_manager_provider=record_provider
    )
    experiment_processor.process()


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument("--dataset")
    parser.add_argument("--asr")
    args = parser.parse_args()
    run_word_wer_pipeline(args.dataset, args.asr)