Making large AI models cheaper, faster and more accessible
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import argparse
from colossalqa.retrieval_conversation_universal import UniversalRetrievalConversation
if __name__ == "__main__":
# Parse arguments
parser = argparse.ArgumentParser()
parser.add_argument("--en_model_path", type=str, default=None)
parser.add_argument("--zh_model_path", type=str, default=None)
parser.add_argument("--zh_model_name", type=str, default=None)
parser.add_argument("--en_model_name", type=str, default=None)
parser.add_argument(
"--sql_file_path", type=str, default=None, help="path to the a empty folder for storing sql files for indexing"
)
args = parser.parse_args()
# Will ask for documents path in running time
session = UniversalRetrievalConversation(
files_en=None,
files_zh=None,
zh_model_path=args.zh_model_path,
en_model_path=args.en_model_path,
zh_model_name=args.zh_model_name,
en_model_name=args.en_model_name,
sql_file_path=args.sql_file_path,
)
session.start_test_session()